Streptococcus pneumoniae and herpes zoster vaccines, summarizes recent developments to improve vaccine efficacy, such as the use of adjuvants or higher antigen dose for influenza, and gives an overview of SARS-CoV-2 vaccine development for older adults. Substantial research is ongoing to further improve vaccines, e.g. by developing universal influenza and pneumococcal vaccines to overcome the limitations of the current strain-specific vaccines, and to develop novel vaccines against pathogens, which cause considerable morbidity and mortality in older adults, but for which no vaccines are currently available. In addition, we need to improve uptake of the existing vaccines and increase awareness for life-long vaccination in order to provide optimal protection for the vulnerable older age group.Preserving good health in old age is of utmost importance to alleviate societal, economic and health care-related challenges caused by an aging society. The prevalence and severity of many infectious diseases is higher in older adults, and in addition to the acute disease, long-term sequelae, such as exacerbation of underlying chronic disease, onset of frailty or increased long-term care dependency, are frequent. Prevention of infections e.g. by vaccination is therefore an important measure to ensure healthy aging and preserve quality of life. Several vaccines are specifically recommended for older adults in many countries, and in the current SARS-CoV-2 pandemic older adults were among the first target groups for vaccination due to their high risk for severe disease. This review highlights clinical data on the influenza,  Low birth rates and higher life expectancy are transforming the age pyramid in Europe towards a much older population. Between 2010 and 2020 the share of the population older than 65 years of age increased by 3 percentage points in the EU (from 17.6 to 20.6%) and is projected to further increase to more than 31% by 2100. The share of those older than 80 years is projected to have a 2.5-fold increase (5.9% to 14.6%) from now until 2100 [Influenza causes approximately 15,000-70,000 deaths annually in Europe, mainly in older adults , and comImmunogenicity of standard TIV is lower in older compared to young adults  and fraiIn placebo-controlled trials enrolling young adults TIV is up to 70% effective against laboratory-confirmed influenza , 22, butAn obvious strategy to improve immunogenicity of vaccines might be to increase the amount of antigen per dose. A higher antigen dose should result in increased uptake and presentation by antigen-presenting cells and therefore in stronger activation of adaptive immune cells. In the US, Canada, Brazil, Australia and the UK, a trivalent high-dose influenza vaccine has been used for several years (HD-TIV). This vaccine contained 60μg hemagglutinin for each strain instead of the standard 15μg. HD-TIV was shown to induce higher anti-hemagglutinin antibody concentrations and seroprotection rates, as well as increased numbers of influenza-specific T cells in older adults compared to TIV , 26. Cli+ T cell response is elevated [An alternative strategy to improve vaccine-induced immune responses is the use of adjuvants in order to protect cohorts, which develop unsatisfactory immune responses after standard immunization (e.g. older adults). Aluminum salts have been used in human vaccines for approximately 100 years in combination with various, but not with influenza antigens. As one of the first modern adjuvants the oil-in-water emulsion MF59, which comprises squalene and the surfactants Tween 80 and Span85 was licensed as an adjuvant in seasonal influenza vaccines for older adults in 1997 . It has also been approved for other age groups including children (6-24 months) and in pandemic influenza vaccines. MF59 induces proinflammatory chemokines and cytokines at the site of injection thereby recruiting innate immune cells and facilitating efficient antigen uptake, enhances differentiation of dendritic cells in the lymph nodes, and is involved in shaping the germinal center reaction , 30. Antelevated . Intereselevated , 35. A melevated .Clinical effectiveness of HD-TIV and aTIV were recently compared directly in two studies. A retrospective cohort study, which analyzed data of persons above 65 years during the 2016/2017 and the 2017/2018 influenza seasons reported that HD-TIV provided better protection from respiratory-related hospitalizations compared to aTIV, with a pooled relative vaccine effectiveness (rVE) of 12%  . In contBoth high-dose and adjuvanted influenza vaccines have recently been modified to contain four instead of three different influenza strains (HD-QIV and aQIV) and have been licensed in many countries. Recent studies confirmed higher immunogenicity of HD-QIV compared to standard QIV  and non-Annual vaccination against influenza is recommended for all adults in many countries, but most recommendations emphasize the particular importance for vulnerable groups, such as older adults. Several countries specifically recommend the high-dose and/or adjuvanted influenza vaccines for older adults. In previous years these guidelines were complicated by the fact that these “improved” vaccines were only trivalent, whereas the standard vaccine had already been available in a quadrivalent formulation. For the season 2021/2022 HD-QIV and aQIV will be available in many countries and are included in specific national recommendations for older adults. As examples, Germany issued its first recommendation for a specific vaccine, namely the HD-QIV, for the 2021/2022 season . In the Next-generation influenza vaccines are being developed. One approach is the use of alternative adjuvants, which might overcome the diminished responsiveness of the aged immune system. As mentioned above, MF59 is used successfully in influenza vaccines and other squalene-based adjuvants have also been tested (summarized in ). AS03 h+ T cells contribute to an efficient immune response in several ways. They have direct effector functions e.g. cytokine secretion and cytolysis in the lung, are important for rapid innate responses and provide help to B cells, which ensures optimal antibody production, as well as to CD8+ T cells. The cytotoxic CD8+ T cells recognize and eliminate infected cells, thereby limiting virus spread in the body. Many of the vaccine candidates for universal influenza vaccines utilize antigens and/or technologies, which aim to elicit robust T cell responses. A comprehensive summary of these approaches has recently been published [Influenza-specific antibodies show some degree of cross-reactivity towards related viral strains and influenza-specific T cells can recognize conserved epitopes. However, clinical data show that a mismatch between vaccine strains and circulating virus strains decreases efficacy and effectiveness of influenza vaccines. Overall influenza vaccine effectiveness is usually 40-60% in years with adequate matching of vaccine and circulating virus strains . But as ublished . It is vublished –59.Streptococcus pneumoniae (pneumococcus) can be classified into more than 90 distinct serotypes based on their polysaccharide capsule of which only a limited number are pathogenic [S. pneumoniae is an increasing problem [S. pneumoniae infection can be non-invasive  or invasive . Incidence of invasive pneumococcal disease (IPD) as well as pneumococcal pneumonia increases with age. S. pneumoniae is the most frequently isolated pathogen causing community-acquired pneumonia (CAP) in older adults. In the US nearly 30,000 cases of invasive pneumococcal disease (IPD) and over 500,000 cases of non-bacteremic pneumococcal pneumonia were estimated to occur every year in persons older than 50 years, resulting in more than 25,000 pneumococcus-related deaths [S. pneumoniae being the most common pathogen accounting for 35% (95% CI: 14%-56%) of all bacterial co-infections [thogenic . Antimic problem . Clinicad deaths . Bacterifections .S. pneumoniae; polysaccharide vaccines (PPV), which contain the purified bacterial capsule polysaccharides, and conjugated vaccines (PCV), for which the polysaccharides are conjugated to carrier proteins. The serotype coverage of the different vaccines is summarized in Table Two types of vaccines are available against 2 responses [S. pneumoniae, the incidence of IPD also decreased in older adults, presumably due to reduced transmission from children to older adults [Purified polysaccharides are T cell-independent antigens, and as such elicit a distinct immune response. Without T cell help, B cell activation and differentiation happen independently of germinal centers resulting in short-term antibody production, a lack of B cell memory and mainly IgM and IgGesponses , 65. Infr adults . A certaTwo different methods are used to quantify polysaccharide-specific antibodies and to determine immunogenicity of the pneumococcal vaccines. ELISA-based methods detect IgG antibodies but no other antibody classes and early ELISA methods were often unspecific. Improved protocols solved this problem, but some older studies need to be interpreted with caution . FunctioWith age, immunogenicity of PPV-23 decreases, as shown by reduced opsonophagocytic activity, alterations in class and subclass usage as well as in somatic hypermutation –76. CurrEfficacy and effectiveness of pneumococcal vaccines have been mainly studied for IPD and in some studies for pneumococcal pneumonia. In an extensive meta-analysis pooled vaccine efficacy/effectiveness (VE) of PPV-23 against IPD and pneumococcal pneumonia was calculated for different types of studies and ranged from 73% against IPD in clinical trials to below 50 % in cohort studies , detoxified pneumolysin derivative (PlyD) and pneumococcal surface protein (PspA) or combinations of those are developed. Many of these vaccine candidates combine the antigens with different adjuvants. Several of these vaccine candidates show promising immunogenicity and safety profiles in early clinical studies and even more are still in pre-clinical development [Universal vaccines against elopment –111.Primary infection with varicella-zoster virus (VZV) usually occurs in childhood and manifests as chickenpox (varicella). Life-long viral latency is established in sensory ganglia, and reactivation of VZV, which can occur throughout life, is usually controlled by T cell responses  and therefore asymptomatic. In situations with reduced CMI, e.g. under immunosuppression or with increasing age, reactivations can manifest as herpes zoster (HZ) if the virus spreads through the sensory nerve to the corresponding dermatome. This results in a typically unilateral, frequently painful, segmented skin rash. A substantial increase of the HZ incidence with age  was reported in a systematic review, which included 130 studies from various countries .Pain occurring or persisting more than 3 months after onset of the rash is referred to as post-herpetic neuralgia (PHN), and is a frequent complication of HZ. PHN is often associated with severe pain, which is very difficult to manage therapeutically and can last for several months resulting in considerable impact on activities of daily living and quality of life , 114. ThA live-attenuated vaccine based on the Oka Merck virus strain is available to prevent primary infection with VZV in children, and the same strain (14-fold higher dose) was also used in older adults to prevent HZ. As a live-attenuated vaccine, it is not suitable for immunocompromised patients, who are at high risk for HZ, but it has a favorable reactogenicity and safety profile in immunocompetent persons including older adults. A second-generation vaccine against HZ contains the viral envelope glycoprotein E (gE) and the adjuvant system AS01B, which consists of 3-O-desacyl-4´-monophosphoryl lipid A  and QS-21, a saponin found in the bark of the tree Quillaja Saponaria, formulated in liposomes, which act as antigen delivery systems. This combination enables uptake of the antigen via endocytosis, activates innate immune cells via the TLR-4 pathway and targets subcapsular macrophages in the lymph node –120, lea+ T cells producing at least two cytokines) increases in more than 90% of the recipients and remains above the CMI-response threshold in 57% three years later. Specific CD4+ T cells persist substantially above pre-vaccination values even 9 years after vaccination [+ T cell responses were rarely detected in this study. Antibody levels also increase substantially and remain over baseline for at least three years. Only minimal differences were observed between age groups at any time point. In contrast to the study with the live-attenuated vaccine, a moderate positive correlation between humoral and CMI responses was observed after vaccination with the recombinant vaccine [+ T cell responses are substantially higher following vaccination with the recombinant vaccine, but even total VZV-specific T cell responses were not superior following vaccination with the live-attenuated vaccine. In addition, the recombinant vaccine induced preferentially memory, but less effector T cells. The authors of this study conclude that gE-specific memory Th1-responses are relevant for protection and that high peak memory T cell responses are necessary for long-term persistence [Both vaccines induce antibody and cellular immune responses, but T cell mediated immunity (CMI) is considered to be essential for protection against herpes zoster, whereas only a minor role is attributed to antibodies. Immunogenicity was investigated in sub-cohorts of the pivotal Phase III trials for both vaccines. It has been shown that baseline VZV-specific T cell responses decline with age and are lower for persons ≥70 compared to those 60-69 years of age, whereas baseline antibody levels are independent of age and did not correlate with CMI . Upon vacination . A slighcination –126. CD8 vaccine . Direct sistence . Antibodsistence .Vaccine efficacy in persons older than 60 years was 51% against HZ and 67% against PHN in the pivotal Phase III randomized, double-blinded, placebo-controlled trial for the live-attenuated vaccine . HoweverThe two pivotal phase III randomized, placebo-controlled clinical trials for the recombinant, adjuvanted vaccine included more than 30,000 participants older than 50 or 70 years, respectively , 135. NoFrailty status was determined for more than 90% of the participants of the two studies, and as expected, prevalence of frailty increased with age. Vaccine efficacy against HZ was above 90% also in the frail and pre-frail sub-cohorts . VaccineIn contrast to the live-attenuated vaccine, the recombinant vaccine is suitable for immunocompromised patients. Safety and immunogenicity have been demonstrated in patients after renal transplantation , in HIV-A clear limitation of the live-attenuated vaccine is that its use is contraindicated for patients under immunosuppression. An inactivated vaccine, which used a heat-inactivated formulation of the Oka Merck virus strain demonstrated 63.8% (95%CI: 48.4-74.6) and 83.7% (95%CI: 44.6-95.2) efficacy against HZ or PHN, respectively in a Phase III trial in hematopoietic stem-cell transplant recipients . HoweverIn the current SARS-CoV-2 pandemic older adults, persons with underlying co-morbidities and obese individuals have the highest risk for severe disease and death from COVID-19 –145. Rep+ T cell responses after one dose of vaccine were slightly lower in the older age group. The age-associated decrease in immunogenicity was more pronounced for CD8+ T cell responses, with cytokine-producing T cells detectable in 51% of the younger and 36% of the older cohort, respectively [First-in-human clinical trials are usually performed in young, healthy adults, but for SARS-CoV-2 vaccines clinical development moved quickly towards the inclusion of older adults. As an example, the phase I dose escalation trial for Spikevax was extended from the original cohort (18-55 years) to also include participants >55 and >70 years  and Comiectively . Phase Iectively . Furtherectively .Safety of all vaccines has been investigated extensively. This summary highlights age-related aspects and therefore mainly relies on the safety data from later stage trails, which included more older participants. The safety profile of the two mRNA vaccines Comirnaty and Spikevax are similar, with local pain at the site of injection being more frequent than redness and swelling. Fatigue, headache, muscle pain and chills are the most frequent systemic events , 156. ThPhase III clinical trials to determine vaccine efficacy included older adults, but particularly for the oldest age groups the number of participants was usually not sufficient for statistical analysis. For the BioNTech/Pfizer vaccine, overall efficacy against symptomatic SARS-CoV-2 infection was 95.0 % (95%CI: 90.0-97.9) after 2 doses with a 3-week interval. Vaccine efficacy did not differ in the age groups 16-55y, >55y, and ≥65y. However, analysis of the oldest age group (≥75y) was not statistically significant with 5 cases of COVID-19 in the placebo and zero cases in the vaccinated cohort, respectively. In this study more than 40% of the participants were older than 55 years, but less than 5% were over 70 years old . ResultsDue to the limited supply of vaccines at the beginning of national vaccination campaigns specific target groups including health care workers and older adults were prioritized and were the first to receive the vaccine. Effectiveness in “real life” has been and is still monitored in many countries. Asymptomatic infections were mainly monitored in health care workers as they are routinely tested for active infection irrespective of vaccination. High effectiveness of the mRNA vaccines was demonstrated already after the first dose and further increased after full vaccination , 166. HoMany factors are relevant for optimal protection. There is evidence that longer time-intervals between the two vaccine doses are beneficial , 172 andIn future years, SARS-CoV-2 vaccines might become part of national vaccination schedules for everybody, or at least for risk groups. First studies are ongoing investigating co-administration of SARS-CoV-2 vaccines with other vaccines, such as influenza or pneumococcal vaccines , and development of combination vaccines (e.g. SARS-CoV-2 and influenza) has started .Many countries recommend regular booster vaccinations against tetanus and diphtheria, sometimes in combination with acellular pertussis and/or inactivated polio for all adults. Other vaccines might be relevant in some countries, e.g. against tick-borne encephalitis in endemic areas. Most recommendations for these vaccines do not mention older adults in particular, but some countries e.g. in Europe Austria, Liechtenstein, France and Portugal advocate shortened booster intervals for older adults. Tetanus- and even more so diphtheria-specific antibody concentrations are frequently below the levels considered to be protective for adults, and are even lower in older age groups –183. In As mobility, financial resources and health of older adults have improved over the last decades, long-distance travel and as a consequence the need for travel vaccines have become increasingly common for this age group. Despite the fact that some tropical diseases, e.g. Japanese encephalitis and typhoid fever are more frequent and severe in older adults , 194, onS. pneumoniae and herpes zoster are available for older adults, and vaccines that are recommended for all adults  are also relevant in old age. Modifications of the vaccines, such as higher antigen dose or adjuvants for influenza vaccines, and optimization of vaccination schedules are strategies to improve vaccine effectiveness for older adults. However, vaccination coverage is still unsatisfactory for many of these vaccines and systematic data on vaccine uptake are not collected in all countries. Barriers to vaccine uptake are manifold and include lack of access, which can be caused by financial or other constraints, and personal decisions against vaccination based on missing information or misinformation regarding risk of disease and benefit of vaccination. To overcome these issues documentation of vaccine uptake in conjunction with data such as age and other risk factors is crucial in order to identify gaps in coverage and develop strategies to specifically target the relevant cohorts. Vaccination documentation is important also on a per-person scale in order to deliver vaccines at the right time and to enable reminder systems.Older adults are at increased risk for severe disease caused by various pathogens and this is particularly evident in the current SARS-CoV-2 pandemic. The last 18 months have also shown that novel vaccines can successfully be developed in a short period of time. Clinical efficacy of COVID-19 vaccines is high, even in older adults. Nevertheless, it seems that immunity and potentially protection wanes faster in older age groups and that additional doses will be required earlier in these cohorts highlighting the importance of including specific age- and risk-groups in clinical and observational studies. Several vaccines against other pathogens, such as influenza, Staphylococcus aureus and Escherichia coli, which are responsible for infections of catheters, prostheses, or surgical wounds and Clostridium difficile, which is the most common cause of nosocomial diarrhea are among the most relevant bacterial nosocomial pathogens [Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter ssp., and Candida spp. could have a substantial impact. Norovirus is the most relevant viral nosocomial infection and outbreaks in hospitals and long-term care facilities are frequent. The disease is characterized by vomiting and diarrhea and can be severe in older adults. In 2016 the World Health Organization stated that the development of a norovirus vaccine should be considered an absolute priority, and vaccine development is ongoing [There are still many pathogens, which cause high morbidity and mortality in the older population, for which no vaccines are available, but would be highly desirable. The risk for nosocomial infections is high for older persons due to an increased frequency of invasive procedures, hospitalization or long-term care, and antibiotic resistance of bacterial pathogens is an increasing problem in these settings. athogens . Several ongoing . A detai ongoing . Respira ongoing . RSV vac ongoing . There aOptimization of existing vaccines and vaccination strategies as well as development of novel vaccines for “old”  and “new” pathogens have the potential to substantially improve health and quality of life in older adults. A detailed knowledge about age-associated changes of the immune system is essential in order to rationally design vaccines which hopefully overcome these limitations, and it is of utmost importance to consider age-related aspects already early in the vaccine development process Table .Table 3


Extracorporeal life support treatments such as extracorporeal membrane oxygenation (ECMO) have been recommended for the treatment of severe acute respiratory distress syndrome (ARDS) patients with coronavirus disease 2019 (COVID-19). To date, many countries, including China, have adopted ECMO as a treatment for severe COVID-19. However, marked differences in patient survival rates have been reported, and the underlying reasons are unclear. This study aimed to summarize the experience of using ECMO to treat severe COVID-19 and provide suggestions for improving ECMO management. The effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the pathophysiology of COVID-19 and the effects of ECMO on the clinical outcomes in patients with severe cases of COVID-19 were reviewed. Recent data from frontline workers involved in the use of ECMO in Wuhan, China, and those experienced in the implementation of artificial heart and lung support strategies were analysed. There is evidence that ECMO may complicate the pathophysiological state in COVID-19 patients. However, many studies have shown that the appropriate application of ECMO improves the prognosis of such patients. To expand our understanding of the benefits of ECMO for critically ill patients with COVID-19, further prospective, multicentre clinical trials are needed. The current outbreak of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected millions of people worldwide . DespiteECMO is initiated in cases of refractory hypoxemia that are unresponsive to conventional care. Veno-venous (V-V) ECMO is mainly used in patients with severe COVID-19-related ARDS, and a small number of patients with circulatory disorders are managed with veno-arterial (V-A) or veno-venous arterial (V-VA) ECMO. The prognosis is often worse in the latter groups of patients. It is worth noting that ECMO can also affect normal physiology and exacerbate coagulation and immune abnormalities in patients with COVID-19 despite having good therapeutic effects  patients with COVID-19, acute hypoxemic respiratory failure of varying severity is a common feature, and its incidence can be as high as 67% . PrelimiThere are two primary phenotypes of hypoxemic respiratory failure: Type L (“non-ARDS”), which is characterized by normal or high compliance, a low ventilation-to-perfusion ratio, low lung weight and low recruitability, and Type H , which is characterized by very low compliance, high lung weight and high recruitability, accompanied by severe hypoxia , 24, 31.In addition to pulmonary complications such as ARDS, SARS-CoV-2 infection can also cause cardiovascular damage, making it the second leading cause of death in COVID-19 patients. The reported incidence of acute myocardial injury has varied from 7 to 28% among hospitalized patients, and high levels of cardiac troponin are associated with more severe disease , 32, 33.COVID-19 patients present with a hypercoagulable state, which is more common and more pronounced in ICU patients. The prevalence of a hypercoagulable state exceeds 30% in all ICU patients, whereas that of pulmonary embolism is 16.7% , 39. EleCOVID-19 patients often present with immune dysfunction and abnormal inflammation activation. Higher-risk subgroups of COVID-19 patients tend to have lymphopenia accompanied by overall leucocytosis and high levels of inflammatory markers  . High ILThe incidence of ischaemic stroke in patients with COVID-19 is 10.3%, and most patients have conventional stroke risk factors. Haemorrhagic stroke is relatively rare, with an incidence of approximately 0.9% –44. The ECMO is a form of extracorporeal life support (ECLS) that is mainly used to oxygenate the blood to temporarily compensate for failing lungs or a failing heart while minimizing further iatrogenic ventilator-induced lung injury (VILI). ECMO operates mainly under two modes, V-V and V-A, depending on the auxiliary organ. In addition, variants of the above modes, such as the V-AV ECMO mode, are available. V-V ECMO is used in patients with respiratory failure only, whereas V-A ECMO is used in patients with both respiratory and circulatory failure.2/FiO2, immunocompromised status, comorbidities, and the need for V-A ECMO.Patients with COVID-19 present with respiratory failure, and the ECMO mode mainly used in these patients is V-V (91%) . HoweverThe most common complications of ECMO in COVID-19 patients include bleeding and thrombosis. In addition to the promotion of thrombosis by COVID‐19, the use of ECMO can also affect blood coagulation function. The incidence of venous thrombosis in COVID-19 patients receiving ECMO is 33%, the incidence of pulmonary embolism is 29%, and the incidence of cerebral haemorrhage is 5%-6%, whereas severe bleeding in these patients is relatively rare , 39, 49.Mechanical-related complications, including pump failure, oxygenator dysfunction, and circuit embolism, have also been reported in COVID-19 patients. Circuit changes, oxygenator failures, pump failures or cannula conditions occur in 28% of patients, as reported by the ELSO Registry of ECMO in COVID-19 , compareRecent studies reported that ECMO can be successfully used in appropriately selected COVID-19 patients with severe ARDS , 52–55. 2/FiO2 ratio was 71.9 (IQR 58.6–87.0) before ECMO initiation, and 58.9% of the patients underwent prone positioning. Old age (> 65 years) has been identified as a risk factor for mortality in critically ill COVID-19 patients.Previous clinical studies from China reported that patients who underwent ECMO had poor outcomes, with mortality ranging from 30 to 83% , 56, 57.2/FiO2 of 60 (IQR 54–68) mmHg before ECMO initiation. Further analysis showed that the estimated 60-day mortality rate was 31% (95% CI 22–42), which is similar to the rate reported in the EOLIA trial and the large prospective LIFEGARD registry of ECMO for severe ARDS not caused by COVID-19 , 6362, 6The lungs are the most vulnerable organs in COVID-19 patients, and most patients have normal cardiac function in the early stage. V-V ECMO is the primary ECMO mode used in patients with ARDS, as it provides a “time window” during which the failing lungs can rest and recover. V-V ECMO provides full or partial extracorporeal pulmonary support by adjusting the blood flow (which can be as high as 7 L/min) . The oxyV-V ECMO drains blood from a femoral venous or internal jugular venous cannula. The blood is then pumped through a membrane oxygenator, and finally, it is returned to the venous system either through a femoral venous or internal jugular venous cannula. A large multi-stage drainage cannula is recommended (such as 23 Fr or greater for adults) to minimize the need for the insertion of an additional drainage cannula at a later stage. The right femoral vein and the right internal jugular vein (which are relatively straight) are often used as the preferred vessels for V-V ECMO catheterization based on the availability of resources, personnel experience and ease of operation . ImpropeV-A ECMO is a form of ECLS that provides temporary mechanical circulatory support and simultaneous extracorporeal gas exchange in patients with severe cardiogenic shock and decompensated heart failure. The initiation of V-A ECMO serves as a salvage intervention in COVID-19 patients with cardiogenic shock or cardiac arrest. The timely initiation of V-A ECMO is recommended prior to the development of multiple organ failure. V-A ECMO drains deoxygenated blood from the right atrium through a femoral venous or internal jugular venous cannula and pumps it through a membrane oxygenator, allowing oxygenation and carbon dioxide removal. The oxygenated blood is then returned to arterial circulation through a cannula placed in a peripheral artery, usually the femoral or subclavian artery. A femoro-femoral configuration is recommended for V-A ECMO cannulation.2 in the upper body than in the lower body), also known as differential hypoxia or two-cycle syndrome, results from a high afterload  and recovered left ventricular systolic function [2) drops below 40 or decreases more than 25% from baseline or a delta-rSO2 between the right radial artery and left radial artery > 15% is detected by NIRS [A common complication of V-A ECMO is hypoxia in the upper body, which can cause severe cerebral hypoxia. Hypoxia in the upper body The initiation of V-VA ECMO as a pre-emptive strategy is not conventionally recommended. It should only be used in experienced centres for patients with suspected acute stress/septic cardiomyopathy or massive pulmonary embolism or associated cardiogenic/obstructive shock that is not responsive to medical therapies. The occurrence of refractory upper body hypoxia in V-A ECMO is also an indication for establishing V-VA ECMO . In the ECMO, a type of ECLS, is a breathing and circulation support technology that supplements the functioning of the lungs and heart. It has been widely used in the treatment of various critically ill patients with respiratory and/or circulatory failure in the past decade. However, the provision of therapy with ECMO during the outbreak of an emerging contagious disease is challenging.In patients with indications for ECMO therapy and without obvious contraindications, ECMO therapy should be initiated in a timely manner. Having a complete understanding of the support provided by different ECMO modes and the differential distribution of oxygen under different ECMO modes, performing a full assessment the patient's heart and respiratory function and selecting the appropriate ECMO mode can improve survival. Several factors, such as sex, age, comorbidities, clinical manifestations and the duration of mechanical ventilation, can affect the outcomes of ECMO , 74.The number of critically ill patients with COVID-19 is increasing rapidly every day, causing a shortage of ECMO devices in some regions. Therefore, it is crucial to prioritize the most eligible patients for ECMO therapy. ECMO should be used preferentially for a certain group of patients  because they have higher survival rates. Governments should invest in more ECMO devices, ventilators and related medical equipment to support more patients.Patients with COVID-19 complicated with severe ARDS have a high mortality rate. The use of ECMO can further complicate the pathophysiological state in COVID-19 patients. However, several studies have reported that the appropriate use of ECMO improves the prognosis of patients. COVID-19 is a major cause of ARDS, which causes most COVID-19-related deaths. This study provides information about the effective use of ECMO in critically ill COVID-19 patients. However, these recommendations should continue to be updated and improved as additional high-quality trials are completed.


Antibody-mediated rejection (ABMR) is the main cause of renal allograft loss. The most common treatment strategy is based on plasmapheresis plus the subsequent administration of intravenous immunoglobulin (IVIG). Unfortunately, no approved long-term therapy is available for ABMR. The current study was designed to analyze the effect of various ABMR treatment approaches on allograft survival and to compare treatment effects in the presence or absence of donor-specific antibodies (DSAs).This single-center study retrospectively analyzed 102 renal allograft recipients who had biopsy-proven ABMR after transplant. DSA was detectable in 61 of the 102 patients. Initial standard treatment of ABMR consisted of plasmapheresis (PS) or immunoadsorption (IA), followed by a single course of IVIG. In case of nonresponse or recurrence, additional immunosuppressive medications, such as rituximab, bortezomib, thymoglobulin, or eculizumab, were administered. In a second step, persistent ABMR was treated with increased maintenance immunosuppression, long-term therapy with IVIG (more than 1 year), or both.p = 0.83). Remarkably, allografts survival rates were comparable between patients treated with the combination of PS/IA and IVIG and those treated with a single administration of IVIG (p = 0.18). Renal transplant patients with ABMR but without DSAs benefited more from increased maintenance immunosuppression than did DSA-positive patients with ABMR (p = 0.01). Recipients with DSA-positive ABMR exhibited significantly better allograft survival after long-term application of IVIG for more than 1 year than did recipients with DSA-negative ABMR (p = 0.02).Overall graft survival among transplant patients with ABMR was <50% after 3 years of follow-up. Compared to the use of PS/IA and IVIG alone, the use of additional immunosuppressive medications had no beneficial effect on allograft survival (The results of our single-center cohort study involving kidney transplant recipients with ABMR suggest that long-term application of IVIG is more favorable for DSA-positive recipients, whereas intensification of maintenance immunosuppression is more effective for recipients with DSA-negative ABMR. Despite all efforts, long-term renal allograft survival is limited to an average of 11 to 15 years  . DSAs dide novo DSAs can develop in nonsensitized patients after transplant. Although ABMR is more common in the late posttransplant course, early ABMR can occur within the first 6 months after transplant , or both, with subsequent intravenous administration of IVIG at a dosage of 0.5–0.8 g/kg over 3 days . If therPretransplant lymphocytotoxic crossmatches were negative for all recipients. For HLA typing of recipients and donors, DNA was isolated from peripheral blood samples with spin columns  or with an automated system using magnetic separation technology . HLA-class I  and II  typing was performed at the first field resolution level with sequence-specific primers (polymerase chain reaction sequence-specific primer method) or alternatively with sequence-specific oligonucleotides  .All patients were screened for anti-HLA antibodies before transplant. Anti-HLA antibody status after transplant was monitored at months 3, 6, and 12 after transplant and annually thereafter. Additional screening was performed if allograft dysfunction occurred. Pretransplant sensitization status was determined with the standard immunoglobulin G (IgG) complement-dependent cytotoxicity test in combination with a Luminex-based LABScreen Mixed beads assay , which was used to identify the antibodies against HLA classes I and II. If the results of the LABScreen Mixed beads assay were positive, anti-HLA antibodies were further characterized in terms of IgG alloantibody specificity for HLA-A, -B, -C, -DR, -DP, and -DQ with LABScreen single-antigen bead (SAB) assays  according to the manufacturer's protocols. All beads with normalized median fluorescence intensity (MFI) values higher than 1.000 were considered to be positive for anti-HLA antibodies. To address a potential effect of interfering antibodies or prozone effects on our MFI analyses, all patient sera included in this study have been treated with ethylenediaminetetraacetic acid (EDTA) prior to Luminex-based assay testing .2 test for categorical variables and with the Mann–Whitney test for continuous variables. Allograft survival among patients with ABMR was illustrated with Kaplan–Meier survival curves and analyzed with the log-rank test. To assess independent factors influencing renal allograft survival, we performed a multivariable Cox regression analysis and calculated the hazard ratio (HR) and the 95% confidence interval (CI). Variables for multivariate analysis were selected based on the results of univariate analysis. For all tests, statistical significance was set at the level of p ≤ 0.05. All data analyses were performed with GraphPad Prism version 6  and IBM SPSS Statistics version 23 .Categorical variables were expressed as numbers and percentages. Comparisons between groups were made with the χOf the 438 renal allograft recipients who underwent allograft biopsy between January 2014 and September 2017, 102 were found to have biopsy-proven ABMR with known DSA status, one patient with ABMR was excluded due to missing DSA status. The remaining 335 renal allograft recipients who received a primary biopsy for cause showed the following results: Borderline rejection (Banff category 3) in 60 and T-cell mediated rejection (Banff category) in 46, Banff category 6 in 201 , Banff category 5 in 1, normal renal tissue in 4, non-representative renal biopsy in 23.Clinical and demographic characteristics of these 102 patients with histologic features of ABMR are summarized in Comparing patients with DSA-positive ABMR and patients with DSA-negative ABMR, we noted that a larger proportion of patients in the DSA-negative group had undergone previous transplants . RecipieOverall allograft survival among all kidney transplant patients with ABMR was <50% at the 3-year follow-up.First, we analyzed the effect of several variables associated with ABMR on allograft survival among the 102 recipients with biopsy-proven ABMR. We selected several relevant factors, such as DSA status, C4d positivity, occurrence of ABMR within the first year after transplant, and histologic signs of various Banff categories in addition to ABMR so that we could evaluate the potential effect of these variables on allograft outcome.p = 0.72, Renal allograft survival rates were comparable between recipients with DSA-positive or DSA-negative ABMR, a finding suggesting that DSA status had no significant effect on allograft loss in the present cohort . The remaining 13 recipients , bortezomib (n = 11), thymoglobulin (n = 9), or eculizumab (n = 3)  . We founp = 0.01, p = 0.02; Renal allograft recipients exhibiting histologic features of biopsy-proven persisting ABMR received increased maintenance immunosuppression, long-term therapy with IVIG for more than 1 year, or both. Increased immunosuppression was defined as a change in the maintenance immunosuppressive regimen or as a switch from dual to triple immunosuppressive therapy. An acceleration of the dosage of maintenance immunosuppressive drugs was not considered for the analysis. Maintenance immunosuppressive therapy was intensified for 28 patients in the study cohort. These 28 recipients exhibited higher rates of allograft survival than did the remaining 71 patients .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This cross-sectional study uses spatial analysis to evaluate social determinants of health and COVID-19-related mortality rates among Black, Hispanic, and White populations living in rural, suburban, and urban communities. How do the associations between structural factors and COVID-19 mortality help explain the disproportionate outcomes experienced by different racial and ethnic groups?In this cross-sectional study of 3142 counties in 50 US states and the District of Columbia, the associations between different measures of social determinants of health and COVID-19 mortality varied across racial and ethnic groups  and different community types .Findings from this study suggest the need for future research that addresses health inequity and guides policies and programs by further exploring the different dimensions and regional patterns of social determinants of health. Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts.To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic.This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic . Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinal-impact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations.County-level characteristics and community health factors  associated with COVID-19 mortality.Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and county-level COVID-19 mortality rate.P < .001), indicating that mortality rates in urban areas were associated with immigrant communities with traditional family structures, multiple accessibility stressors, and housing overcrowding. Higher COVID-19 mortality rates were also associated with preventable hospital stays in rural areas  and higher socioeconomic status vulnerability in suburban areas . Across all community types, places with limited internet access had higher mortality rates, especially in urban areas .Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large group of older adults (26 of 33 [78.8%]), and had limited access to quality health care (24 of 33 [72.7%]). In urban areas, the mixed immigrant cohesion and accessibility index was inversely associated with COVID-19 mortality (coefficient [SE], –23.38 [6.06]; This cross-sectional study found an association between different SDOH measures and COVID-19 mortality that varied across racial and ethnic groups and community types. Future research is needed that explores the different dimensions and regional patterns of SDOH to address health inequity and guide policies and programs. Instead, racial disparities in health largely emanate from the inequitable access to social, economic, and physical or built environmental conditions resulting from racism in the US. Specifically, racism interacts with and exists within societal structures and systems to shape the major SDOH, including the housing, labor, and credit markets as well as the education, criminal justice, economic, and health care systems.8 This inequity occurs at both interpersonal and structural levels, positioning stigmatized racial and ethnic minority populations at greater risk for poor outcomes.Evidence shows that social determinants of health (SDOH), the structural conditions that characterize where people live, work, and play, are substantial factors in racial and ethnic health disparities, including disparities in COVID-19 infection and mortality rates.9 In the context of the COVID-19 pandemic, researchers have identified structural racism as a factor in the disproportionate burden on Black individuals,10 Indigenous peoples,11 and Hispanic or Latinx communities,12 yet relatively few analyses have explicitly reported an association between SDOH and COVID-19 mortality rates. In this cross-sectional study, we used measures of SDOH in US counties with the highest percentages of racial and ethnic minority groups as well as the highest mortality rates as a proxy to examine whether SDOH were associated with COVID-19 mortality across racial and ethnic minority groups and communities.There is a demonstrated need to consider the role of these structural factors of inequality in understanding health outcome disparities.13 suggesting that state-level estimates can mask heterogeneous population patterns and make community-level impacts difficult to evaluate.14 Initial explorations of CDC data underscore this challenge. 15 the most granular level at which both race- and age-disaggregated data are currently available. Data in most HHS regions show higher death rates for Hispanic and non-Hispanic Black populations compared with non-Hispanic White populations. Clearer disparities are shown when comparing death rates for the working-age population aged 18 to 65 years. The associations between these rates are not uniform across HHS regions, indicating racial and spatial heterogeneity at the regional scale. This heterogeneity likely persists below the regional and state levels; eFigure 1 in the One challenge in quantifying the implications of structural racism for COVID-19 outcomes is that the US Centers for Disease Control and Prevention (CDC) does not report race-disaggregated COVID-19 data below the state level. The Modifiable Areal Unit Problem in geography highlights issues of different findings produced by varied levels of aggregation,16 or high mortality17 with all other counties. Although these approaches highlight the disproportionate burden experienced by racial and ethnic minority groups and the potential contribution of SDOH, these approaches miss the potential heterogeneity in different groups in different contexts  as well as fail to account for the contagious nature of COVID-19.County-level data provide more fine-grained information, but race- or age-disaggregated COVID-19 data at this scale are, to our knowledge, unavailable nationally. Researchers address such issues of limited data in varying ways, such as comparing counties with high proportions of a racial and ethnic group18 given that the virus is highly transmissible between individuals  and has exhibited uneven spread across geographic areas and populations .19 An exploratory spatial data analysis (ESDA) approach helps address these research challenges.21 Using ESDA, we explored the spatial and racial disparities in county-level COVID-19 mortality rates across national-scale data sets during the first year of the pandemic to gain insights into the dimensions of structural racism closely associated with COVID-19 mortality. The spatial perspective allowed us to examine the potential heterogeneity in different racial and ethnic groups across rural, suburban, and urban contexts and to explicitly account for contagious outcomes across county borders.This contagiousness requires analysis to make the spatial effects explicitSTROBE) reporting guideline.This observational, cross-sectional study included all counties in 50 states and the District of Columbia (N = 3142), drawing on county-level COVID-19 mortality data reported by the CDC from January 22, 2020, to February 28, 2021. Racial and ethnic and other demographic data as well as other SDOH measures were sourced from publicly available data sets. The study was deemed exempt from review and the requirement for informed consent by the institutional review board at The University of Chicago because it used publicly available, deidentified data. We followed the Strengthening the Reporting of Observational Studies in Epidemiology . We calculated the number of COVID-19 deaths per 100 000 population using the 2019 American Community Survey (ACS) 5-year estimates. This number served as the outcome variable in the regression analysis.The primary outcome was county-level COVID-19 mortality rates. We included the first 2 months in 2021 because the COVID-19 vaccines became effective after 2 weeks of being fully vaccinatedWe focused on the 3 largest racial and ethnic groups in the US according to the 2019 ACS 5-year estimates: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. Race and ethnicity were self-identified in the ACS. We calculated the percentage of the adult population (aged ≥18 years) for each racial and ethnic group for each county.5 which were extracted from an adapted socioecological model of health that spans individual, interpersonal, organizational, and community metrics. Using a principal component analysis, Kolak et al5 created 4 indexes to account for 71% of the variance in their SDOH model, which included 15 variables in the continental US. Specifically, the 4 indexes were (1) the socioeconomic advantage index, which is dominated by socioeconomic status factors and in which a low value is characterized by a high percentage of the population living in poverty, with a racial and ethnic minority status, without a high school diploma, and without health insurance; (2) the limited mobility index, in which a low value is characterized by a high percentage of older adults (≥65 years) and people with disabilities; (3) the urban core opportunity index, in which a high value reflects a highly urbanized population with more opportunities along with a high per-capita income and high living costs such as a high rent burden; and (4) the mixed immigrant cohesion and accessibility index, in which a lower value is characterized by more immigrant populations with traditional family structures and multiple accessibility stressors such as crowded housing and lack of health insurance. These measures expanded beyond a single dimension of socioeconomic disadvantages and were found to have a validated association with premature mortality in Chicago, Illinois.5 For this analysis, we aggregated Census tract–level indexes to the county level.To capture multiple dimensions of SDOH, we used 4 indexes developed by Kolak et al,24 Counties with more than 50% urban tracts were classified as urban counties, counties with more than 50% suburban tracts as suburban, and counties with more than 50% rural tracts as rural.Additional variables for measuring structural factors were included in this study to capture potential social factors that were not covered in the 4 indexes but were crucial to COVID-19 mortality and provide more contextual information to help in understanding and interpreting the patterns in the 4 indexes. As principal components, the 4 SDOH indexes are orthogonal to each other by construction to reflect most information in multiple variables, but they may be difficult to interpret at the same time owing to the compression of correlated variables. Thus, we included specific variables to help with this interpretation. In particular, we included age distribution , rural-urban context, and multiple community health factors  and delay in mask mandates; for the second variable, we counted the number of days that a state-level mask mandate was initiated after the occurrence of more than 200 new confirmed cases per 100 000 populations per 14 days. eTable 1 in the Additional community-level health factors were identified from theoretical evidence and literature on neighborhood characteristics and COVID-19 mortalityBecause no previous studies have explored the study question  at the national scale, we adopted an exploratory approach with multiple streams of inquiries to identify patterns that we did not expect to see. We started with colocation analysis and visual analytics to identify counties that were severely affected by COVID-19 during the study period , particularly areas in which each racial or ethnic group in the study was experiencing high COVID-19 mortality rates. We then analyzed the potential community characteristics of these areas that are statistically associated with their high mortality rates. This initial step allowed us to refine our understanding of the data-generating processes, which were then operationalized in the spatial regression using raw data. In particular, we deployed spatial regime regression models to examine the associations of multiple aspects of structural factors with the county-level COVID-19 mortality.All statistical tests were 2-sided with a significance level of α = .05, with Bonferroni correction for multiple comparisons. All statistical analyses were performed using R, version 4.0.2 , and GeodaSpace, version 1.2 (GeodaSpace).27 and has been applied across various fields to study spatial associations between different events.30 For the present analysis, if a county (1) had mortality rates in the top quintile for 100 days or more over the year (the 100 days did not need to be consecutive) and (2) was in the top quintile of adult populations of a particular racial or ethnic group, then we labeled it as a concentrated longitudinal-impact county. The top quintile of population was different for each racial or ethnic group: 14.2% for the Black or African American group, 10.2% for the Hispanic or Latinx group, and 94.5% for the non-Hispanic White group.We used colocation analysis to identify counties with consistently high COVID-19 death rates that had a high proportion of residents of a particular racial or ethnic group compared with other counties. Colocation analysis is rooted in the association between geographic locations and economic activities and processes31 identified 26% of counties  that were considered hot spots for COVID-19 transmission for at least 1 day, wherein the median number of days (not necessarily consecutive) that a county met the hot spot criteria was 10.Although consecutive-day hot spots  would likely indicate a more severe COVID-19 impact, the number of counties that met this selection criteria would be small , making interpretation difficult. Previous research has used similar approach. For example, from March 8 to July 15, 2020, Oster et alWe summarized mortality rates, SDOH indexes, and structural factors for each concentrated longitudinal-impact county and the remaining non–concentrated longitudinal-impact counties for comparison. For each measure included , we implemented analyses of variance to test for statistically significant differences in SDOH indexes and structural factors across concentrated longitudinal-impact counties using Bonferroni correction for multiple comparisons.34 In the present analysis, the dot density technique visualized the within-county variation of racial and ethnic composition according to the ACS census estimate using 1 dot to represent 120 people by racial and ethnic group assorted by Census tract level. Each map panel illustrated a different racial and ethnic group, which was visualized as a dot density map. These dots were then assigned a color scheme according to the number of days that county had a high COVID-19 mortality rate . Using this method, we assumed that mortality was distributed equally across all racial and ethnic groups within the same county; this was a conservative approach given that disparity is known to exist even within counties.26 At the same time, population typologies  can be visually highlighted so that variations between counties are made more apparent, although within-county variation of mortality is hypothesized as a conservative estimate of equal distribution. We also used choropleth maps with fixed bins to geovisualize the number of days that each county had a high death rate, with the concentrated longitudinal-impact counties highlighted.Because race-disaggregated COVID-19 data are not available below the county level for all states, we used dot density mapping as a visual analytic technique to illustrate where racial or ethnic groups tended to live at the Census tract level and where COVID-19 death data were recorded at the county level. Such dot maps have recently been widely used to delineate spatial distributions of discrete geographic features, such as social demographic characteristics.35 This approach is often adopted in regional science to capture structural instability.38We hypothesized that distinct patterns of concentrated longitudinal-impact counties would emerge across urban, suburban, and rural contexts. We modeled urban, suburban, and rural counties as different spatial regimes, reflecting different processes through which SDOH dimensions were associated with COVID-19 mortality. The SDOH as independent variables may uniquely be associated with the COVID-19 mortality outcome in different spatial regimes. Each regime was then characterized by different values of regression coefficients in such spatial regime models.I statistic and found that COVID-19 mortality rates had a statistically significant spatial autocorrelation . This result invalidated traditional statistical analysis (including log-likelihood ratios), which assumes an independent, identically distributed phenomenon. We thus adopted spatial regression to account for spatial autocorrelation. Such spatial econometric approaches have been adopted to study spatial epidemiologic processes40 and are increasingly common in relevant policy and public health literature,43 including COVID-19 studies at smaller regional scales.46 We operationalized a second-order queen contiguity spatial weight in spatial models to model the spatial interdependence; that is, we allowed an interaction between a county and its neighbors as well as the neighbors of its neighbors  estimates, which do not consider spatial autocorrelation to observe collinearity among all factors. First, we included 4 SDOH indexes because they were orthogonal to each other by construction and reflected most information across various SDOH dimensions. Second, we added community characteristics to the model to capture factors that were associated with COVID-19 but were not covered by the 4 SDOH indexes. Variables that were correlated with the 4 indexes were excluded to avoid multicollinearity, including age distribution, income inequality, uninsured rate, primary care physicians, and severe housing problems. Third, we fit the data with spatial error model to account for the spatial interaction effect using generalized method of moments estimation.We reported white SEs for all OLS estimates and heteroskedasticity-robust SEs for all spatial error models. All models were implemented in GeoDaSpace, version 1.2.Among the 3142 counties included in this study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) were identified as concentrated longitudinal-impact counties with the largest share of Black or African American population among US counties (n = 74 997 322), 198 (6.3%) were concentrated longitudinal-impact counties with the largest share of Hispanic or Latinx population among US counties (n = 98 493 610), and 33 (1.1%) were concentrated longitudinal-impact counties with the largest share of non-Hispanic White population among US counties (n = 1 085 094). Another 2611 counties  were not identified as concentrated longitudinal-impact counties. A total of 489 254 COVID-19-related deaths were reported. We stratified mortality rates, SDOH indexes, and structural factors by concentrated longitudinal-impact counties for each racial or ethnic group . DensityBy design, all concentrated longitudinal-impact counties had significantly higher COVID-19 mortality rates than other counties during the study period. The median (IQR) deaths per 100 000 population were 231.43 (181.80-289.14) in a concentrated longitudinal-impact county with a large Black or African American population compared with other counties, 218.84 (173.31-287.39) in a concentrated longitudinal-impact county with a large Hispanic or Latinx population compared with other counties, and 251.79 (223.58-290.50) in a concentrated longitudinal-impact county with a large non-Hispanic White population compared with other counties. In contrast, the median (IQR) mortality rate in non–concentrated longitudinal-impact counties was 128.55 (75.66-191.72) per 100 000 population. Although all of the concentrated longitudinal-impact counties were disproportionately affected by COVID-19, the outcomes stratified by their populations were not the same.First, although the 33 concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties had a higher mortality rate per 100 000 population, many more counties were identified as having Black or African American and Hispanic or Latinx concentrations, indicating that concentrated longitudinal-impact counties with large Black or African American and Hispanic or Latinx populations compared with other counties had higher aggregated COVID-19 mortality than all concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties . Second, many concentrated longitudinal-impact counties with the largest shares of Black or African American (233 of 347 [67.1%]) and Hispanic or Latinx (110 of 198 [55.6%]) populations among US counties had a higher percentage of working-age people than the national median level. In contrast, 26 of 33 concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties (78.8%) had a higher percentage of people aged 65 years or older compared with the national median. Third, 23 of 33 concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties (69.7%) were located in rural areas, whereas a large proportion of the concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties (114 of 198 [57.6%]) were mainly located in urban areas. Concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were a mixture of rural, suburban, and urban areas.These concentrated longitudinal-impact counties also had substantial variation in SDOH indexes. A large proportion of concentrated longitudinal-impact counties with a large Black or African American population compared with other counties had socioeconomic advantage index (318 of 347 [91.6%]), limited mobility index (221 of 347 [63.7%]), and urban core opportunity index (211 of 347 [60.8%]) values that were lower than the national median values. Meanwhile, in most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties, the socioeconomic advantage index (170 of 198 [85.9%]) and mixed immigrant cohesion and accessibility index (115 of 198 [58.1%]) were lower than the national median, but the urban core opportunity index was higher (131 of 198 [66.2%]). A high urban core opportunity index may reflect a higher risk of COVID-19 infection through greater potential workplace exposure given that the index features urbanized populations with more working opportunities. In contrast, most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties had limited mobility index (23 of 33 [69.7%]) and urban core opportunity index (25 of 33 [75.8%]) values that were lower than the national median values. This observation was consistent with the finding that concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were mostly located in rural areas and had higher percentages of residents aged 65 years or older.In addition to these SDOH indexes, other social factors were uniquely associated with COVID-19 mortality across the different concentrated longitudinal-impact counties. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties (297 of 347 [85.6%]) had higher income inequality than the national median. Many concentrated longitudinal-impact counties with large Black or African American (227 of 347 [65.4%]) and Hispanic or Latinx (130 of 347 [65.7%]) populations compared with other counties also had a higher-than-the-national-median percentage of younger people (<65 years) without insurance. Twenty-four of 33 concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties (72.7%) had a higher ratio of residents to primary care physicians than the national median ratio. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties (281 of 347 [81.0%]) showed greater preventable hospital stays than the national median. Severe housing problem rates were higher than the national median level in concentrated longitudinal-impact counties with large Black or African American (266 of 347 [76.7%]) and Hispanic or Latinx (170 of 198 [85.9%]) populations compared with other counties. In addition, most concentrated longitudinal-impact counties with large Black or African American (244 of 347 [70.3%]) and non-Hispanic White (21 of 33 [63.6%]) populations compared with other counties had higher percentages of households without access to the internet.On dot density maps , we obseP < .001; global Chow test in spatial error model: 205.22; P < .001), with most factors having significantly different coefficients across different spatial regimes. According to the Chow test results, this finding was especially true for factors associated with preventable hospital stays , socioeconomic advantage index , and limited mobility index . The models also explained the most variance in COVID-19 mortality rates in urban areas (adjusted R2 = 0.35) and the least variance in rural areas (adjusted 2R = 0.13). Evidence for spatial dependence was found .Both OLS estimates . Second, in rural areas, the measure of preventable hospital stays was associated with mortality rates . The mask mandate policy variable, which was statistically significant in OLS estimates for urban areas , was not significant in the spatial error model .First, places with more limited internet access had higher mortality in all spatial regimes . The limited mobility index was associated with COVID-19 mortality in rural areas , but it was inversely associated with COVID-19 mortality in suburban areas . These observations suggest that higher COVID-19 mortality rates were associated with rural areas with younger populations and/or fewer persons with disabilities, in contrast to suburban areas with older populations and/or more people with disabilities. The mixed immigrant cohesion and accessibility index was inversely associated with COVID-19 mortality in urban areas , which suggests that the higher the number of immigrant populations with traditional family structures, multiple accessibility stressors, and housing overcrowding, the higher the COVID-19 mortality rates.The SDOH indexes also showed distinct patterns in different spatial regimes. For the socioeconomic advantage index, greater vulnerability was associated with higher COVID-19 mortality rates in suburban areas , and then we examined the associations between SDOH and COVID-19 mortality in different spatial regimes . In the initial step of analyzing concentrated longitudinal-impact counties, we found that those counties with a large non-Hispanic White population were composed of more rural counties with significantly smaller total populations compared with the more urban, more densely populated counties with a high concentration of Black or African American and Hispanic or Latinx groups. This contrast was further validated in the second step of the spatial regression analysis, which revealed that different dimensions of SDOH were associated with high COVID-19 mortality rates across rural, suburban, and urban areas. These results underscore how place and people intersect within multifaceted power structures that produce and reproduce inequity in health outcomes.55We believe this study also extends the findings from previous studies on structural health inequity by focusing on SDOH and structural factors that characterize systemic disadvantages experienced by racial and ethnic minority groups. To this end, we intentionally avoided treating race and ethnicity as preexisting conditions or as explanatory variables on the right-hand side in regression models.56 this study further highlighted this association in urban areas and connected it with our finding that most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas. Moreover, we found that these counties had a high percentage of working-age people without health insurance and who were more likely to be exposed to COVID-19 infection. This finding is consistent with previous findings in Latinx adults who were more often at risk for contracting COVID-19 because of work requirements and hesitant about going to a hospital because of economic and immigration concerns.57In urban areas, internet access and the mixed immigrant cohesion and accessibility index were important factors in mortality rates. Consistent with previous research that found that severe housing problems were associated with higher COVID-19 incidence and mortality,In suburban areas, higher mortality was associated with lower socioeconomic advantage index and limited mobility index, indicating higher poverty rates in these areas along with higher percentages of older adults and/or people with a disability. More research is needed to understand the mechanisms regarding how SDOH contributes to COVID-19 mortality and/or other health outcomes in suburban areas.58; the significant association thus highlighted the critical role of access in high-quality health care in rural areas. The association between limited mobility index and COVID-19 mortality was unexpected. A possible explanation for this association is that the limited mobility index captures a potential higher mobility among those with less physical restrictions from age or disability because a low limited mobility index characterizes a high proportion of adults 65 years or older and people with disabilities. We found that most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties had a large number of older adults living in rural areas with limited access to health care. Given the opposite coefficients of the limited mobility index in rural vs suburban regime, future research should examine (1) the mechanism through which older populations are vulnerable to COVID-19 and (2) the association between mobility (measured as movement or traveling) and the spread of COVID-19. A recently published study has started to discuss higher COVID-19 mortality rates in rural areas,59 but the underlying mechanisms are still understudied. The results of the present study shed a light on this important area for future research.In rural areas, higher COVID-19 mortality was associated with more preventable hospital stays and higher limited mobility index. The preventable hospital stay measure considered both quality and access26 Adopting an asset-based approach,61 we believe this finding suggests that more awareness is needed about the essential asset of technological access to reliable information, remote work, schooling opportunities, resource purchasing, and/or social community. Populations with limited internet access remain understudied and are often excluded in pandemic research.Furthermore, internet access was a significant factor in all communities, an observation that extends similar findings from previous work.63 the results of this study suggest a possibility that the mask mandate has implications at a regional level rather than a county level.We also showed statistical evidence for spatial dependence. The mask mandate policy factor was no longer significant after we accounted for spatial heterogeneity and spatial dependence. Although other studies have reported conflicting findings regarding the association between mask mandate and COVID-19 mortality rates,Clearly, SDOH dimensions matter for health outcomes, but the results of this study add nuance to this assumption by demonstrating that SDOH potentially shape health in unique ways, depending on a community’s rural and urban contexts as well as its racial and ethnic makeup. We found that non-Hispanic White populations in rural areas and Hispanic or Latinx populations in urban areas were especially vulnerable to COVID-19 mortality, whereas Black or African American populations across rural and urban contexts fared poorly  during the first year of the pandemic. For urban, rural, and suburban communities, some dimensions of SDOH seemed to be more consequential for COVID-19 mortality rates, pointing to the social levers that might play the biggest role in moving the needle on population health in different types of communities. For future public health interventions and policy proposals, this analysis offers one way to apply a chisel rather than a hammer to identifying, prioritizing, and tackling social factors associated with deeply entrenched health inequities across racial and ethnic groups and spaces.Understanding health inequities is also important for developing and implementing equitable, place-based interventions. This study calls for similar, future research to guide policies and programs at the county or regional level. A more complex model that uses geospatial and temporal patterns to reflect spatial effects and dynamic community aspects , in addition to existing SDOH measures and human behaviors, is needed for future analysis.65 Second, this cross-sectional study used ESDA, and thus the results should not be interpreted as causal. Additional longitudinal analyses are needed to evaluate the implications of SDOH for racial and spatial disparities in COVID-19 mortality. Third, the county-level scale may not capture the full picture of the affected populations, and further research is needed when race-disaggregated data become available at granular spatial scales.This study has several limitations. First, we excluded analyses for other racial and ethnic groups, such as American Indian and Alaska Native and Asian people, because of the small proportion of these populations in the data set. However, research that includes or focuses on these groups is warranted given the disproportionate COVID-19 burden that these groups have also experienced.Fourth, although we attempted to capture a more persistent and stable pattern by including the data from the entire first year of the COVID-19 pandemic, we acknowledge the potential confounding factor of vaccines being available at the end of 2020. To check this, we ran the analysis without the first 2 months of 2021 and included the results in eTable 3 in the This cross-sectional study found that SDOH measures were associated with spatial and racial inequity in COVID-19 mortality rates in the US. This association varied for Black or African American, Hispanic or Latinx, and non-Hispanic White populations and in different rural and urban contexts. To address health inequities and to guide policies and programs at the county or regional level, future study is needed into the different dimensions and regional patterns of SDOH.


Various guidelines are in place for management for COVID-19 and pulmonary tuberculosis (PTB) in pregnancy. However, to the best of our knowledge, there are no significant guidelines for the management of COVID-19 and PTB co-infection in pregnancy. Pregnancy being an altered physiological state, the use of various drugs and their outcomes are altered. Here we present two cases of COVID-19 and PTB co-infection in pregnancy which were managed successfully. The COVID-19 pandemic has had a major impact on healthcare delivery in India and worldwide. Knowledge about COVID-19 management is still evolving, and the risk of infection and its impact on health are being extensively studied in the population. However, the risks to foetus due to COVID-19 during pregnancy are not fully known, and co-infection with pulmonary tuberculosis (PTB) can further complicate the situation. Guidelines for management of PTB in pregnancy have been well established. The CDC suggests that antitubercular treatment should be started early when the probability of TB is moderate to high, since untreated disease presents a greater hazard to mother and foetus than when treated. Various regimens for management of latent tuberculosis and active tuberculosis include daily and weekly regimens lasting up to 9 months. Guidelines for drug-resistant TB and drugs to avoid in pregnancy are also in place. ) that categorises them into low-, moderate- and high-risk categories. [Pregnant women should follow similar strategies to avoid exposure to egories. Co-infection with tuberculosis in this scenario can further complicate matters since it presents with similar symptoms though with a longer incubation period. Tuberculosis was found to be prevalent in 0.37–4.47% of COVID-19 patients, and those with active tuberculosis infection have more than twice the risk of contracting severe COVID-19 infection. The MOHFW, India provides the following guidance regarding screening of COVID-19 and TB co-infection. A bidirectional TB-COVID screening strategy promotes COVID-19 testing for all diagnosed TB patients and TB screening for all COVID positive patients. For those with confirmed COVID-19 and presenting with constitutional symptoms of tuberculosis, in close contact with a TB case and past history of PTB, chest X-ray and sputum Nucleic Acid Amplification Test (NAAT) – CBNAAT/TrueNat) should be offered.  However,Both patients in our series presented in late pregnancy and underwent sputum testing for AFB and Nucleic Acid Amplification Test (NAAT) along with imaging as indicated. For Case 1, a chest X-ray was done using an abdominal shield, and for Case 2, HRCT thorax was done prior to bronchoscopy.The antenatal, intrapartum and postnatal care for pregnancy with COVID-19 infection is illustrated in Data regarding the treatment for COVID-19 in pregnant women are limited, and most trials evaluating the use of the antiviral remdesivir have excluded pregnant women. Results from a compassionate-use programme involving 86 pregnant women with confirmed COVID-19 infection who received 10 doses of injectable remdesivir were suggestive of high recovery rates and a low rate of serious adverse effects. Guidelines have been formulated by the CDC for management of tuberculosis in pregnancy with regimens for latent TB infection, TB disease and HIV-related TB disease. For latent TB infection, the commonly used regimens are the either the 4-month daily regimen of rifampin (RIF) (4R), a 3-month daily regimen of isoniazid (INH) and RIF (3HR), 6- or 9-month daily regimen of INH (6H or 9H) with pyridoxine (vitamin B6) supplementation. For those with TB disease, initial treatment is with INH, RIF, and ethambutol (EMB) daily for 2 months, followed by INH and RIF daily, or twice weekly for 7 months . Streptomycin should be avoided since it can cause harmful effects on the foetus. Pyrazinamide is not preferred since its effects on the foetus are unknown. Kanamycin, amikacin, capreomycin and fluoroquinolones are also contraindicated in pregnancy. For the Indian scenario, a collaborative framework for management of tuberculosis in pregnant women has been laid out by the MOHFW. During the ANC period, a standard treatment regimen must be followed for drug-sensitive TB. A 32 weeks USG focussing on diagnosis of foetal complications must be performed, as well. In the case of drug resistant TB, the patient should be advised for medical termination of pregnancy if the duration of pregnancy is less than 20 weeks. For those unwilling for MTP or not eligible for MTP (duration of pregnancy more than 20 weeks), a modified conventional MDR-TB regimen may be started, clearly explaining its risks to the mother and foetus. [Both patients in our series were diagnosed as drug-sensitive TB and were started on a standard weight-based regimen under DOTS comprising HRZE for 2 months (intensive phase) followed by HRE for 4 months (continuation phase) along with vitamin B6 supplementation and a high protein diet.Regarding steroid use in COVID-19 pregnancy, recent evidence supports the early use of short-course glucocorticoids for those patients requiring oxygen support or mechanical ventilation.  However,Supportive treatment for COVID-19 was provided as per standard protocol. Acetaminophen was preferred over NSAIDs in our series on an SOS basis for fever, based on limited evidence and anecdotal reports raising concerns for possible negative effects of NSAIDS in young non-pregnant COVID-19 patients.  ProphylaPregnant patients with COVID–TB coinfection must be closely monitored for complications such as acute respiratory failure, ARDS, pneumonia, sepsis due to COVID-19 and haemoptysis, pneumothorax, bronchiectasis and chronic pulmonary aspergillosis due to PTB.The treatment of COVID–TB coinfection can be challenging in pregnancy. Recent data support the use of remdesivir, and patients in our series tolerated the combination of antiviral and antitubercular treatment well. However, further randomised controlled trials are needed to establish the safety and efficacy of the same.COVID-19 is an emerging, rapidly evolving situation and we recommend healthcare professionals to review the latest official guidelines from local governments and health organisations.


These findings may inform guidance for limiting transmission and emphasize the value of testing to identify community-acquired infections.We characterized common exposures reported by a convenience sample of 202 US patients with coronavirus disease during January–April 2020 and identified factors associated with presumed household transmission. The most commonly reported settings of known exposure were households and healthcare facilities; among case-patients who had known contact with a confirmed case-patient compared with those who did not, healthcare occupations were more common. Among case-patients without known contact, use of public transportation was more common. Within the household, presumed transmission was highest from older ( Coronavirus disease (COVID-19) was first identified in Wuhan, China, in December 2019 (This activity was reviewed by the Centers for Disease Control and Prevention (CDC) and was conducted consistent with applicable federal law and CDC policy. Forms were approved under the Office of Management and Budget (no. 0920–1011).The case investigation form (CIF) is a supplemental questionnaire designed by CDC in January 2020 to collect detailed demographic and epidemiologic information about a convenience sample of US COVID-19 case-patients reported by participating states. This purposive nonprobability sample was selected at the state level from persons identified through care-seeking, surveillance, or contact tracing as having COVID-19; infection with severe acute respiratory coronavirus 2 (SARS-CoV-2) was confirmed by reverse transcription PCR. CDC provided guidance for selection of case-patients across a range of ages and symptom severities , but states individually controlled sampling. The CIF was completed by state or local health department personnel or by CDC staff through case-patient or proxy interviews, along with medical record reviews (when relevant).Case-patient demographic information included age, sex, race, ethnicity, and occupation. Workplace settings were classified according to 2012 census industry codes. Clinical information included underlying conditions, symptoms, symptom onset date, dates of medical visits, and outcome . For hospitalized case-patients, information was requested about whether the patient had been admitted to an intensive care unit, whether oxygen was received, admission and discharge dates, diagnosis, and location. Questions about exposure included whether in the 14 days before illness onset the case-patient had known exposure to a case-patient with laboratory-confirmed COVID-19 (COVID-19 contact) and, if so, the relationship and setting of the exposure. Case-patients were also asked about their exposure risks (activities and possible exposures in the 14 days before illness onset) including travel; friends, acquaintances, co-workers, or family members with fever or respiratory symptoms; close contact with  any ill persons; attendance at a mass gathering ; public transportation use; attendance or work at a school or daycare; school or daycare attendance by household members; close contact with a contact of a laboratory-confirmed case-patient; close contact with someone with fever, acute respiratory illness, or both who had traveled internationally in the previous 14 days; and time in a healthcare setting as an employee, patient, or visitor.The CIF also collected data on the case-patient’s household members, defined as anyone who stayed overnight in the same residence as the case-patient during the 14 days before the case-patient’s illness onset until the date of interview. Case-patients were asked for household members’ age, sex, relationship to the case-patient, and whether each person had “experienced fever or respiratory symptoms  within 14 days before or after the COVID-19 patient’s illness”; if yes, date of illness onset was collected. When the CIF was designed in January 2020, the most commonly reported COVID-19 signs and symptoms were fever and respiratory symptoms, and guidance for mitigation measures within households had not been widely distributed.2 or Fisher exact tests, as appropriate. Continuous variables were compared by using t tests for normally distributed data and Wilcoxon rank sum tests otherwise. p<0.05 was considered significant. Analyses were conducted in SAS version 9.4 (https://www.sas.com) and R (https://www.r-project.org).We compared exposures between those reporting known close contact with a COVID-19 case-patient in the 14 days before illness onset and those reporting no known contact. Categorical variables were compared by using χ>2 members (including the CIF subject) if the CIF subject had experienced >1 symptom (to enable identification of the first ill person [index case-patient] in the household), and symptom status was provided for >1 other household member. We required that the earliest symptom onset date in the household be >1 calendar day before symptom onset in subsequent case-patients (to limit effect of co-exposures outside the home) and that the earliest onset date in the household be >3 days  before the interview . We considered presumed household transmission to have occurred if >1 household member, in addition to the CIF subject, was reported as having fever or respiratory symptoms. The person with the earliest symptom onset date in a household was considered the index case-patient, regardless whether SARS-CoV-2 testing had been performed. Any members of a given household not identified as the index case-patient are hereafter referred to as household contacts.We separately assessed presumed household transmission by using information about household members provided by the interviewed COVID-19 case-patient (CIF subject). In the absence of SARS-CoV-2 testing data for all household members, we used reported signs and symptoms  as a proxy for symptomatic COVID-19 infection . We analyzed households of >18 years) to avoid collinearity with familial relationship and index case-patient age.We calculated the overall household attack rate for symptoms as the number of symptomatic household contacts divided by the total number of household contacts with reported symptom status, with Wilson score 95% CI, and the serial interval as the time from symptom onset in the index case-patient to first symptom onset in a household contact. We investigated age and sex of the index case-patients and their contacts, household size, and relationship of the contact to the index case-patient as possible correlates of contact symptom status by using generalized estimating equation logistic regression with households as the cluster and individual symptom status as the outcome; we used an exchangeable correlation matrix and robust SEs. We excluded household contacts missing symptom status from this analysis. We examined models for collinearity and reduced if necessary. We did not include hospitalization status of the index case-patient in models because of collinearity with index case-patient age. We dichotomized contact age  with 202 laboratory-confirmed COVID-19 case-patients with symptom onset during January 14–April 4, 2020. Age of COVID-19 case-patients in the sample ranged from <1 to 95 years, almost all were symptomatic , and 1 in 3 was hospitalized for management of COVID-19 symptoms. Of the 202 case-patients, 34 (17%) reported having diabetes mellitus and 48 (24%) reported hypertension.A total of 82 (41%) case-patients reported known contact with a laboratory-confirmed COVID-19 case-patient in the 14 days before symptom onset. The most commonly reported exposure setting was the household ; within the household setting, the most frequently reported source of COVID-19 exposure was the spouse or partner of the COVID-19 case-patient . The second most reported exposure setting was healthcare ; 14 of the 20 persons exposed in the healthcare setting were healthcare workers, 4 were seeking care for unrelated medical issues, and 2 were visitors.Among persons reporting no known COVID-19 contact, 20/84 (24%) reported having close contact with an ill person. Persons with no known COVID-19 contact worked in a variety of industries, most commonly healthcare ; professional/office settings ; education ; and accommodation, food, or other services  . In comp>1 possible exposure . They required hospitalization more frequently than those reporting >1 possible exposure , and were significantly more likely to report >1 underlying medical condition . They were much more likely to report having diabetes mellitus .Of the 202 case-patients, 23 (11.3%) reported no known contact with a confirmed case-patient, no travel within 14 days before illness onset, and none of the exposure risks assessed. These persons ranged in age from 21 to 88 years and were significantly older than those reporting >1 household members and were included in our household analysis; in 48 (70%) households, the CIF subject was the first or only symptomatic person in the household . Included households ranged in size from 2 to 16 persons (median 4 persons) and comprised a variety of household types ; household size and members’ ages, sexes, and relationships were interrelated. Presumed transmission was more frequently observed in larger households   . Within = 0.005) .Among 201 household contacts, 193 had data on symptom status, of which 62  were symptomatic. Sensitivity analysis results showed a similar plausible range of attack rates (21%–39%). The median serial interval was 3 days (range 1–10 days).>65 years of age (9 households) (>45 years of age (vs. index case-patients 18–44 years of age) after adjustment for contact age, contact sex, household size, and relationship of the contact to the index case-patient  or seholds) , panel A-patient . Adult c-patient , panel B-patient . The sym-patient . Among t>65 years of age), only 2 were symptomatic.Illness severity of the index case-patient could not be assessed in multivariable models because of low sample size and correlation with age. However, among 12 household contacts of 10 index case-patients requiring hospitalization  index case-patients than among contacts of index case-patients 18–44 years of age. Independent of index case-patient age, parents of index case-patients were significantly more likely than other household members to report development of symptoms consistent with COVID-19.In this convenience sample of 202 early laboratory-confirmed COVID-19 case-patients, predominantly identified before widespread mitigation measures in the United States, the most commonly reported settings of known exposure were households and healthcare facilities (primarily as a workplace). Within the household, presumed transmission by age of index case-patient followed a U-shaped pattern and was significantly higher among contacts of older (https://www.medrxiv.org/content/10.1101/2020.08.19.20177188v1). We found that presumed transmission was highest among contacts of older index case-patients (>65 years of age), even when controlling for contact age category, relationship, and household size; however, our sample size was insufficient to control for underlying conditions or hospitalization status of the index case-patient or for detailed age category of the household contact, which may have confounded this relationship because evidence suggests that older adults are more susceptible to COVID-19 . These findings may be explained by the fact that SARS-CoV-2–infected children may have similar or higher viral loads than adults  of case-patients in our sample did not report contact with a laboratory-confirmed COVID-19 case-patient in the 14 days before illness onset. Among case-patients without known COVID-19 contact, travel and public activities were more common, although only public transportation use was significantly higher when this group was compared with case-patients with known COVID-19 contact. Public transportation has not been identified as a major source of SARS-CoV-2 transmission  may also have been affected by the timing of the investigation because public awareness regarding measures to mitigate within-household transmission  was probably lower in the early stages of the US epidemic. Information was not collected on the specifics of known COVID-19 exposure, such as mask wearing or social distancing in the home or other exposure settings, because these were not common practices during survey design. The use of a convenience sample may have also affected findings regarding presumed household transmission, such as if selection were biased toward inclusion of more severe cases or larger investigations. >1 household member attended school or daycare in the 14 days before illness onset in the CIF subject, suggesting a possible outside source of infection. Of note, similar methods are frequently used for studies of influenza (A second limitation is that SARS-CoV-2 infection in most household members was not laboratory-confirmed, so household members with other causes of illness could have been misclassified as COVID-19 case-patients and those with asymptomatic SARS-CoV-2 infections misclassified as non–case-patients. The possibility of misclassification of children may have been higher, given that young children frequently experience respiratory symptoms (Last, our sample size was limited by state capacity for participation and data completeness. We did not have sufficient sample size to control for all possible confounders, such as index case-patient signs/symptoms, clinical characteristics, or detailed contact age category, so residual confounding is possible. The lower sample size also limited the precision of our estimates.Our findings underline the exposure risk associated with work in a healthcare setting and within the household, as previously documented (Case investigation form used in study of patterns of virus exposure and presumed household transmission among persons with coronavirus disease, United States, January–April 2020.Supplemental methods and results for study of patterns of virus exposure and presumed household transmission among persons with coronavirus disease, United States, January–April 2020.