Cervical cancer still poses a significant global challenge. Developed countries have mitigated this challenge by the introduction of structured screening programmes and, more recently, the HPV vaccine. Countries that have successfully introduced national HPV vaccination programmes are on course for cervical cancer elimination in a few decades. In developing countries that lack structured screening and HPV vaccination programmes, cervical cancer remains a major cause of morbidity and mortality. The HPV vaccine is key to addressing the disproportionate distribution of cervical cancer incidence, with much to be gained from increasing vaccine coverage and uptake globally. This review covers the history and science of the HPV vaccine, its efficacy, effectiveness and safety, and some of the considerations and challenges posed to the achievement of global HPV vaccination coverage and the consequent elimination of cervical cancer. One of the most extraordinary stories in medical research is that of Henrietta Lacks, an African American woman who died from cervical cancer seventy years ago, at the age of thirty-one. “HeLa cells”, as they are commonly referred to, are the cells which were collected from her cervix in 1951 shortly before her death; these were the first established in vitro immortal cancer cell line [In the originally biopsied HeLa cells, German virologist Harald zur Hausen in the early 1980’s discovered the presence of HPV-18 ,3. It isHPV now forms the basis of both primary and secondary cervical cancer preventative measures. Most cervical screening programmes worldwide utilise HPV detection as a primary screening tool, in keeping with the World Health Organisation (WHO) recommendations . HPV vacThe combined effect of HPV vaccination and cervical screening should effectively make cervical cancer a rare occurrence, yet it remains a leading cause of cancer deaths globally . WorldwiWe review the natural history of HPV infection and its association with cervical cancer, the different types of HPV vaccine and studies looking into their efficacy, effectiveness and safety. We also review the implementation of the HPV vaccine globally, with a focus on the barriers faced by countries with a low vaccine uptake.Papillomaviridae family. It is the most common sexually transmitted infection worldwide and it is estimated that most sexually active individuals will be infected with HPV at least once in their lifetime [HPV is a double-stranded DNA virus which belongs to the lifetime . Infectilifetime   regulates gene expression and replication, the early (E) region encodes for proteins which are required for HPV gene expression, replication and survival, and the late (L) region encodes for viral structural proteins . The virThe majority of women infected with HPV will clear it within a few years. An estimated 10–20% of women will have persistent HPV infection ,21. From® ), a quadrivalent vaccine which targets HPV-6, HPV-11, HPV-16 and HPV-18, conferring protection against genital warts, which are most commonly caused by HPV-6 and HPV-11. In 2007, a bivalent vaccine, Cervarix® , was licensed, which targets HPV-16 and HPV-18. Gardasil 9® ) is a nonavalent vaccine licensed in 2014 that targets HPV-6, HPV-11, HPV-16, HPV-18, HPV-31, HPV-33, HPV-45, HPV-52 and HPV-58 [® , was developed, which utilises Escherichia coli to produce HPV-16 and HPV-18 L1 VLPs [® was licensed for use in China in 2020 and prequalified by the WHO in 2021. Finally, a recombinant bivalent HPV vaccine  targeting HPV-16 and HPV-18 was also licensed for use in China in 2022 and prequalified by WHO in 2022 [This understanding of HPV-induced carcinogenesis alongside the availability of VLPs has allowed various prophylactic HPV vaccines to be developed. The first to be licensed in 2006 was Gardasild HPV-58 ,22. Thes L1 VLPs . Cecolin in 2022 . Table 1 in 2022 .The vaccines have a similar mode of action based on VLPs, a recombinant, noninfectious assembly of the L1 HPV capsid protein. VLPs are antigenically identical to infection-causing HPV virions , such thPrior to licensure, all HPV vaccines underwent clinical trials to determine efficacy, effectiveness and safety. A WHO convention in 2003 determined appropriate HPV vaccine trial endpoints: it was agreed that ethical and time constraints could not allow for cervical cancer to be an appropriate trial endpoint, given that participants under follow-up during the trial period would receive treatment of any cervical precancerous lesions detected . Agreed The phase 3 efficacy trials conducted for HPV vaccines all included younger women aged 15 to 26. These trials were multinational and included thousands of participants, with the trial design and conduct led by the respective manufacturers. The results from these trials are summarised in ® quadrivalent HPV vaccine, with results published in 2007 [The FUTURE I and II trials assessed the efficacy of the Gardasil in 2007 . Over 12 in 2007 .A subset of European participants from the FUTURE II trial were followed up for fourteen years, with no cases of HPV-16- or HPV-18-associated high-grade cervical dysplasia noted in follow-up period (vaccine efficacy of 100%) . SeroposA double-blinded randomised trial of the quadrivalent HPV vaccine in a Japanese population of women aged 18 to 26 similarly found a high efficacy against vaccine-type high-grade cervical disease .® bivalent HPV vaccine [® vaccine or the hepatitis A vaccine. After a three-year follow-up period, vaccine efficacy against HPV-16 or HPV-18-associated high-grade CIN was 92.9% [The PATRICIA trial was the first to assess the efficacy of the Cervarix vaccine ,36. Overas 92.9% .®. After a four-year follow-up period, vaccine efficacy was 89% against HPV-16- or HPV-18-associated CIN2+ [The Costa Rican Vaccine Trial (CVT) was a second, large prelicensure trial investigating the efficacy and safety of Cervarixed CIN2+ . A longeed CIN2+ .® vaccine was also studied in a population of >6000 Chinese women aged 18 to 25 showing a vaccine efficacy of 100% in HPV-naïve participants [The Cervarixicipants .® 9 vaccine was assessed in a multinational double-blind trial in women aged 16 to 25 [® HPV vaccine. Vaccine efficacy against high-grade cervical disease associated with HPV-31, HPV-33, HPV-45, HPV-52 and HPV-58  was 97.1%; the number of cases per 10,000 person-years was 0.5 in the nonavalent group versus 18.1 in the quadrivalent group. The incidence of abnormalities associated with HPV-6, HPV-11, HPV-16 and HPV-18  was comparable between both groups of participants. Furthermore, the immunogenicity of the nonavalent vaccine with respect to HPV-6, HPV-11, HPV-16 and HPV-18 was comparable to that of the quadrivalent vaccine [The efficacy of the nonavalent Gardasil16 to 25 . Over 14 vaccine , with an vaccine . The aut® vaccine recruited over 7000 female participants aged 18 to 45, in multiple centres in China between 2012 and 2013. The control group received the hepatitis E vaccine. Vaccine efficacy against high-grade genital disease and persistent infection associated with HPV-16 or HPV-18 were 100% and 97.3%, respectively [® vaccine is ongoing in Bangladesh and Ghana, with results expected in 2023 (NCT04508309).The efficacy trial for the bivalent Cecolinectively ,44. Part® vaccine and the bivalent Cervarix® vaccine have both been trialled in older females, a group likely to have reduced efficacy since vaccine efficacy declines with prior HPV exposure. The FUTURE III trial evaluated the efficacy of the quadrivalent vaccine in over 3800 women aged 24 to 45. Vaccine efficacy against vaccine-type CIN1+ was 88.7% in HPV-naïve women and 30.9% in all women [® vaccine’s efficacy in women aged > 25. Vaccine efficacy against combined endpoint of vaccine-type 6-month persistent infection and CIN1+ was 90.5% in the per protocol group and 86.5% in the total vaccinated cohort. Estimated vaccine efficacy against vaccine-type CIN2+ was high but insignificant due to low numbers [The quadrivalent Gardasilll women . Anotherll women . The VIV numbers .While these studies support the use of the HPV vaccine in older females, the effectiveness of the vaccine in this group is less than in adolescents: because the incidence of HPV infection declines with age , older f® vaccine and the quadrivalent Gardasil® vaccine [In many countries, there has been a move to HPV-based cervical screening, meaning that many women will already be known to have had a previous HPV infection. It is therefore important to define the efficacy of the HPV vaccine in this group. Most of the HPV vaccine clinical trials included in the total vaccinated cohort participants who, at the time of recruitment, were positive for HPV DNA or seropositive for HPV antibodies. Unsurprisingly, these groups had lower vaccine efficacy compared to HPV-naïve participants. Vaccine efficacy in seropositive, DNA-negative participants, i.e., those with previous but no current HPV infection, was summarised in a meta-analysis which pooled data from trials on the bivalent Cervarix vaccine . Against vaccine . These fPeople with HIV are known to have lower levels of immunity, which make them more susceptible to persistent HPV infection. A few studies have investigated the efficacy and safety of the HPV vaccine in this population, showing a 100% seroconversion rate following vaccination with no adverse outcomes . HoweverIn males, HPV is associated with a range of anogenital and oropharyngeal diseases—over 90% of anal cancers, over 70% of oropharyngeal cancers and up to 48% of penile cancers are associated with HPV . HPV vac® vaccine, the nonavalent Gardasil 9® vaccine did not undergo clinical trials in men prior to licensure. Rather, immunogenicity studies were done which showed that the nonavalent vaccine elicited immune responses similar to the quadrivalent vaccine against HPV-6, HPV-11, HPV-16 and HPV-18 [® has been licensed for use in men [® vaccine against persistent oral HPV infection [Unlike the quadrivalent Gardasild HPV-18 . Based oe in men . In the nfection .The prelicensure HPV vaccine trials explored protection conferred by the vaccines against nonvaccine subtypes, i.e., cross-protection, with all vaccines demonstrating partial cross-protection against nonvaccine-type infection and disease. The FUTURE I and II trials of the quadrivalent vaccine assessed cross-protection against ten other HPV subtypes—31, 33, 35, 39, 45, 51, 52, 56, 58 and 59. These showed some cross-protective effect against HPV infection and low-grade CIN, most marked against HPV-31, but not against high-grade CIN .® also assessed the cross-protective effects of the bivalent vaccine against nonvaccine-type persistent infection and CIN2+ [® trials indicate cross-protective effect lasting at least 11 years [The PATRICIA and Costa Rica trials of Cervarixnd CIN2+ . A high nd CIN2+ ,61. Long11 years ,63.® and nonavalent Gardasil® vaccines [As with all vaccines, the safety of the HPV vaccine was evaluated in prelicensure trials and continues to be evaluated in surveillance systems worldwide following licensure. Data on HPV vaccine safety are robust and have consistently shown no concerns ,65,66,67vaccines . In vaccvaccines . Followivaccines .® and quadrivalent Gardasil® vaccines in various countries showed a low rate of serious adverse events [In vaccine clinical trials, there was no difference in rates of serious adverse events between vaccine and control groups ,67. Natie events . Most ofe events . There he events ,68.The HPV vaccine is not currently recommended in pregnancy, but safety data from this group have been obtained from prelicensure trials, clinical trials and surveillance systems where women were vaccinated during pregnancy or became pregnant shortly after vaccination. None of these found any association between vaccine administration and adverse pregnancy outcomes including spontaneous abortion, foetal loss and congenital abnormalities . FurtherFinally, the safety of the vaccine with regards to the development of autoimmune disease, venous thromboembolism and neurological conditions has been studied in various contexts, with no association found between the HPV vaccine and these conditions . The eviDespite these robust safety data, concerns about vaccine safety have impacted vaccine uptake in several countries. A notable example of this is Japan, who introduced HPV vaccination into their routine national immunisation schedule in April 2013. Due to physical symptoms including pain and motor impairment reported by vaccinated girls, the vaccination programme was suspended ten weeks later in June 2013. The vaccine remained available; however, its proactive recommendation was discontinued causing a reduction in vaccine coverage from 70% to less than 1% . A modelIn the initial ten years following the HPV vaccine introduction, several population-level studies assessed the real-world effectiveness of the vaccine on HPV-16/HPV-18 infection, anogenital warts and high-grade CIN. In 2019, findings from these were summarised in a systematic review and meta-analysis . Data fr® HPV vaccine nationally in 2009, and was one of the first countries, in 2020, to report on cervical cancer outcomes following vaccine introduction. Their national data showed a remarkable 88% reduction in cervical cancer incidence in women who had been vaccinated prior to age 17, and a 53% reduction in cervical cancer incidence in women vaccinated between the age of 17 and 30 [Ultimately, the aim of the HPV vaccine is to reduce the burden of HPV-associated cancers, and with longer-term population data increasingly emerging, a few studies have been able to report on this outcome. Sweden introduced the quadrivalent Gardasil7 and 30 .In the UK, the bivalent vaccine was introduced in England in 2008, and data on vaccine effectiveness against cervical cancer were published in 2021. Population data from England showed an 87% reduction in cervical cancer incidence in women vaccinated at age 12 to 13, a 62% reduction in women vaccinated at age 14 to 16 and a 34% reduction in women vaccinated at age 16 to 18 . The autAnother national study in Denmark published in 2021, where the HPV vaccine was introduced into the childhood vaccination programme in 2009, reported a high vaccine effectiveness against cervical cancer. The incidence rate ratio was 0.14 in females vaccinated under the age of 17, and 0.32 in females vaccinated between age 17 and 20, when compared to unvaccinated females. Mirroring vaccine efficacy data, the effectiveness of the vaccine was reduced when administered at an older age .HPV vaccines were initially licensed with a recommended three-dose schedule, and the prelicensure trial protocols included three vaccine doses, which demonstrated a high efficacy against vaccine-type CIN2+ and vaccine-type persistent HPV infection. This led to a three-dose regimen being recommended by the WHO and national governing bodies.® bivalent vaccine, carried out a post hoc analysis investigating the vaccine efficacy in women who received less than three doses of the bivalent HPV vaccine. Interestingly, they found that women who received less than three doses of the vaccine had a similar vaccine efficacy against persistent HPV-16/HPV-18 infection, relative to the women who received the per-protocol three doses; this protection lasted for up to ten years [The Costa Rica Vaccine trial group, who conducted a prelicensure trial for the Cervarixen years ,79,80. Aen years .These findings were of huge significance, as a reduced dosing schedule has important public health implications, easing both financial and logistical barriers to the introduction of HPV vaccination programmes. A single-dosing schedule would significantly reduce supply and storage issues and increase compliance. Even with a modest assumed single-dose vaccine efficacy of 80%, there would be (projected) millions of averted cases of cervical cancer . Thus, sA group In India, the Indian HPV vaccine study group, designed a randomised trial to compare vaccine efficacy between one-, two- and three-dosing schedules. Trial plans were interrupted in 2010 when the Indian government suspended HPV vaccination. Consequently, the design was changed to an observational cohort study consisting of >12,000 participants aged 10 to 18. There were over 4000 participants in each dose category . Early dAnother study, the ESCUDDO trial, is an ongoing randomised double-blind design comparing the vaccine efficacy of a one- versus two-dosing schedule of the bivalent and the nonavalent HPV vaccines . Over 20Similar randomised controlled trials are ongoing in various African countries to investigate the efficacy of a single-dosing vaccine schedule including the DoRIS trial in Tanzania (NCT02834637), the HANDS trial in Gambia (NCT03832049) and the KEN SHE trial in Kenya (NCT03675256) . PrelimiWith the evidence pointing towards the high efficacy of a single dose of the HPV vaccine, the Joint Committee on Vaccination and Immunisation (JCVI) in the UK has recently recommended a single HPV vaccine dose in their routine adolescent and MSM vaccination programmes . The WHOEven following treatment for CIN, women remain susceptible to reinfection with HPV and have been shown to be at increased risk of developing recurrent CIN and HPV-associated cancers ,95. TherA systematic review was recently published, which evaluated 22 studies reporting on HPV infection and the risk of HPV-associated disease following surgical management of HPV-associated genital disease in vaccinated individuals . AlthougSince HPV vaccines became available in 2006, countries have progressively introduced the vaccine into their national immunisation schedules. The WHO initially recommended HPV vaccines in 2009, using a three-dosing schedule to girls aged 9–14 years . In 2014As of March 2022, 60% of WHO member states have introduced the HPV vaccine into their national immunisation schedule . The majStrategies to deliver the HPV vaccine include school-based programmes, healthcare facility-based programmes, and outreach/campaign programmes. School-based HPV vaccination programmes have been successful at achieving a high HPV vaccine coverage as demonstrated in several countries. Australia was one of the first countries to implement a national HPV vaccination programme in 2007. This was a government-funded, school-based immunisation programme, offering three doses of the quadrivalent vaccine to 12-to-13-year-old girls. In 2013, the programme was expanded to include boys, and in 2018, changed to two doses of the nonavalent vaccine . Since tThe UK similarly introduced a government-funded school programme aimed at 12-to-13-year-old girls in 2008. The triple dosing schedule was changed to a two-dose schedule in 2014, and the vaccination of 12-to-13-year-old boys was included in 2019 . Prior tIn the United States, routine HPV vaccination for girls aged 11 to 12 was recommended as a three-dosing schedule in 2006. This also included catch-up vaccination for women up to the age of 26. In 2011, routine vaccination was recommended for males aged 11 to 12. In 2016, the standard dosing schedule was reduced to two doses . HPV vacUnsurprisingly, many LLMICs have not been able to introduce the HPV vaccine into national immunisation schedules, due to financial and infrastructural constraints. As of March 2022, 114 out of 145 (78.6%) high-income and upper-middle-income countries have introduced HPV vaccination, whereas only 20 out of 80 (37.5%) low-income and low-middle-income countries have introduced HPV vaccinations nationally . Many ofIn Asia, several countries have been able to add HPV vaccination to their national programmes, such as Thailand, Sri Lanka, Bhutan and the Maldives . In ChinAs of 2022, gender-neutral HPV vaccination schedules are present in 39 WHO member states, and many high-income countries have shifted/are shifting into an era of equity of access to HPV vaccination for all genders ,114. DueThe impact of the HPV vaccine on cervical cancer incidence can only be realised with a high vaccine coverage, and several barriers continue to hinder this. Unfortunately, the countries with the highest cervical cancer burden and therefore in most need of the HPV vaccine face the greatest barriers. Addressing these barriers are key to achieving the full benefit of the vaccine.Vaccine cost is a significant barrier, especially in LLMICs where the introduction of national HPV vaccination programmes is not financially feasible without external support. Gavi, the vaccine alliance, is a global public–private partnership which works with manufacturers to reduce the cost of vaccines to burdened countries, particularly LLMICs. They introduced a programme in 2012 to enable Gavi-eligible countries to introduce HPV vaccination programmes nationally at a negotiated cost of <$5 per dose, versus the usual >USD 100 per dose . There w® vaccine and Walvax Biotechnology’s vaccine, and it is anticipated that this, alongside a ramp-up of production of currently licenced vaccines, will help reverse vaccine shortages by 2023 [Since 2018, there has been a worldwide shortage of HPV vaccines resulting in significant supply constraints. This resulted in adjustments to planned vaccine introduction programmes, which particularly affected LLMICs. The shortages also led WHO’s SAGE to suspend recommendations to vaccinate males and multiage cohorts, in order to reduce the impact of the vaccine shortage . These a by 2023 ,118.Another huge barrier to HPV vaccination which considerably affects LLMICs is the requirement for cold-chain preservation for current HPV vaccines, which adds to already high costs. One way to address this is via lyophilization, which would dehydrate vaccine components and allow transfer of a frozen powder form at higher temperatures . Alterna® in children aged 4 to 8 years (NCT05329961).The HPV vaccine is targeted at adolescent/school-age children, who are a harder group to reach compared to the age group targeted by childhood immunisation programmes. The use of school-based vaccination programmes helps to circumvent this; however, many LLMICs do not have funded school health programmes, which require additional costs and manpower . FurtherGlobally, the COVID-19 pandemic has affected existing HPV vaccination programmes and halted the introduction of new programmes via the closure of schools and suspension of routine immunisation programmes. This has affected other vaccination programmes, and many are still recovering from the impact of the pandemic .Vaccine hesitancy has a huge impact on HPV vaccine uptake globally. Misinformation on safety concerns about the vaccine, and an unfounded association of HPV vaccine use with sexual promiscuity are common drivers behind vaccine hesitancy . A combiDespite the high efficacy of prophylactic HPV vaccines, worldwide prevalence of high-risk HPV infection remains high, mainly due to the low global vaccine uptake and pre-existing HPV infection. This means the elimination of HPV infections and associated diseases could take decades still. Due to their mechanism of action, by inducing a humoral response to prevent an initial HPV infection, prophylactic HPV vaccines cannot have a reliable therapeutic effect . This haListeria-based ADXS11-001 [There are no licensed therapeutic vaccines yet, although several have undergone phase 2 and 3 clinical trials for use in the treatment of CIN and cervical cancer. VGX-3100 is one of such, a DNA-based therapeutic vaccine targeting the E6 and E7 proteins of HPV-16 and -18. Results from a phase 2 clinical trial showed histopathological regression from CIN2/3 to CIN 1 in 49% of vaccinated participants at six months . None ofXS11-001  are in lXS11-001 .In trial settings, therapeutic HPV vaccines have also been combined with other anticancer agents, such as antibodies against programmed death-ligand 1 (PD-L1) and programmed death-1 receptor (PD-1), in the treatment of advanced and recurrent cervical cancer. PD-L1 is an immune checkpoint inhibitor peptide which binds to its receptor PD-1. PD-1 and PD-L1 are expressed by many tumour cells, promoting immune evasion, and they are thus important immunotherapy targets . A phaseTherapeutic vaccines have shown moderate effectiveness against CIN and HPV-associated cancers, but this has been less than anticipated, especially given the high effectiveness of the prophylactic vaccine . One proWe are now 16 years following the licensure of the first prophylactic HPV vaccine, and the efficacy, effectiveness and safety of the vaccine is no longer in question. The main factor limiting the vaccine’s impact is a deficient population coverage . The addAnother interesting concept called FASTER suggests combining HPV vaccination with HPV-based screening in women aged up to 50 . Using t®, is already helping to drive vaccine costs down and increase availability. In the long term, the development of additional cheaper vaccines with less cold-chain dependence will increase HPV vaccine coverage and success. Furthermore, the gradual endorsement of single-dosing schedules will further reduce costs and improve full-dose coverage globally.Equity of access to the HPV vaccine, particularly in LLMICs, is a prerequisite for advancing sustainable HPV vaccination globally. Affordability, political buy-in and addressing cold-chain challenges are all ways to achieve this. The local development of biosimilar vaccines, such as CecolinFrom a racial and ethnic perspective, there remain concerns regarding vaccine equity given ethnic and racial variations in HPV genotype prevalence, which may limit the effectiveness of the vaccine in certain nonwhite populations . The comCervical screening of vaccinated women is still recommended, as there remains the potential for disease caused by nonvaccine oncogenic HPV subtypes. Where it was previously theorised that vaccination against the common oncogenic HPV subtypes would result in an increase in the prevalence of the less common, nonvaccine oncogenic subtypes, early studies indicated that there was no evidence of “type replacement”, i.e., the replacement of the common oncogenic HPV subtypes with the less common ones . Due to The comprehensive approach to cervical cancer control consists of a triad of primary, secondary and tertiary preventative measures. With the highly efficacious prophylactic vaccine, existing cervical screening measures and an anticipated effective therapeutic vaccine, alongside established treatment methods, achieving cervical cancer elimination is within reach. A focus on increasing the coverage and uptake of the HPV vaccine globally will certainly accelerate the attainment of this goal.


GAS –Group A streptococcal infectionsiGAS –invasive Group A streptococcal infectionsCFR –case fatality rateUKHSA –United Kingdom Health Security AgencyWHO –World Health OrganizationECDC –European Centre for Disease Prevention and ControlEditorialSince the beginning of December 2022, unusually high numbers of cases and deaths among children have been reported across the United Kingdom (UK) and other regional European countries like Ireland, France, Netherlands, Spain, and Sweden  1,2]. T,2. T1,2]The United Kingdom has been the worst affected country by this sudden rise. As of 7th December 2022, England alone has reported over 6,600 cases of scarlet fever (an illness that mainly affects children caused by GAS infections) in a period of just 12 weeks (averaging around 550 new cases per week) along with another 652 cases of invasive GAS infections. About 60 cases of deaths have been confirmed in the same period with a mean case fatality rate (CFR) of 9.92% across the country. Age-based stratification has revealed the highest CFR amongst 10-14 years old (27.3%), followed by elderly aged ≥75 years (16.3%). Scotland, on the other hand, has reported cases that were like those observed at the peaks in previous pre-COVID-19 pandemic years .Fig. 2Ma1Streptococcus pyogenes, commonly referred to as Group A beta-haemolytic Streptococcus, is a Gram-positive, non-motile, resident bacteria of the normal human skin, nasopharyngeal, and anogenital tract microflora. Under the microscope, S. pyogenes is visualized as occurring in pairs or chains of multiple round-to-ovoid cocci, each approximately 0.6-1.0 μm in diameter . Fo. Fo10]. 2S. pyogenes requires the administration of antibiotic therapy , with penicillins being the first choice ..The currFurthermore, COVID-19 related global lockdowns had significantly reduced social interactions and confinements in small spaces (classrooms), whilst accelerating the adoption of non-pharmaceutical interventions (NPIs) like hand hygiene, use of face mask and other. These positive measures helped in keeping the load of many viral and bacterial paediatric infections low during the pandemic ,23. HoweNow that the pandemic-era restrictions have been lifted, the increase in social mixing  and confinement to indoor spaces due to winter can be a plausible explanation of this sudden rise. Additionally, since GAS notifications were lower during pandemic time, we now have a double cohort of non-immune children interacting with the bacteria, thereby causing infections . This, nIn conjunction with the immune-debt theory, another theory proposes that COVID-19 infections (in both symptomatic and asymptomatic cases) could have led to immune dysregulation in children , thereby leaving children susceptible to subsequent infections. As for increased iGAS notifications, the UKHSA suspects it to be consequence of heightened scarlet fever activity. Genomic analysis has previously shown a crossover of strains associated in both presentations ,25.4https://www.mimslearning.co.uk/courses/espresso-cpd-invasive-group-a-streptococcus).A multisectoral and multiprong strategy is needed to curb the rising cases of GAS infections. Firstly, measures for primary prevention need to be introduced including epidemiological investigations and improved surveillance systems. Prompt identification and notification of clusters require a coordinated response from general practitioners (GPs), pharmacists, parents and schools since they are the first contact with children. This requires public education and outreach. A free-to-complete online module is available for GPs for training  . AdditioStreptococcus pneumoniae and Staphylococcus aureus in mice following immunization by live attenuated influenza vaccine [S. pneumoniae does not belong to GAS group of bacteria.We would like to also draw attention towards the need to tame the misinformation campaigns that have somewhat become non-separable from any infectious endemic. Following the widespread rise in new cases and deaths, multiple false pieces of information are being circulated on various social media platforms. Amongst them, the most circulated piece is a study published in 2014 that reported on the possible increase in colonization of  vaccine . The aut vaccine . HoweverIn conclusion, we would urge the public-at-large to follow official guidelines, be vigilant of early red-flag symptoms of GAS infections, do not fall for misinformation, get vaccinated against COVID-19 and influenza and undertake other precautionary measures as discussed above. Authorities have expressed hope that moving forward, as life returns to pre-pandemic standards, the immune debt would be paid off and cases would begin to drop.Not applicable. All data presented in the paper has been collected from open-source platforms with proper citation and/or from media sources.The authors declare no conflicts of interest in regards with the present paper.The present paper didn't receive any external funding and was self-supported by the authors.NJ and EL conceptualized the paper whilst all authors were involved in data collection, writing, correction, and finalizing of the final draft. Visualization was done by NJ whilst supervision was done by AR. All authors have read and agreed to the final version for publication.


Vaccination against coronavirus disease 2019 (COVID-19) has contributed greatly to providing protection against severe disease, thereby reducing hospital admissions and deaths. Several studies have reported reduction in vaccine effectiveness over time against the Omicron sub-lineages. However, the willingness to receive regular booster doses in the general population is declining. To determine the need for repeated booster vaccinations in healthy individuals and to aid policymakers in future public health interventions for COVID-19, we aim to gain insight into the immunogenicity of the additional bivalent booster vaccination in a representative sample of the healthy Dutch population. The SWITCH ON study was initiated to investigate three main topics: i) immunogenicity of bivalent vaccines after priming with adenovirus- or mRNA-based vaccines, ii) immunological recall responses and reactivity with relevant variants after booster vaccination, and iii) the necessity of booster vaccinations for the healthy population in the future.https://clinicaltrials.gov/, identifier NCT05471440. Vaccination against coronavirus disease 2019 (COVID-19) has contributed greatly to providing protection against severe disease, thereby reducing hospital admissions and deaths . HoweverBivalent vaccines that contain both the ancestral S protein, to boost previously induced immune responses, and the Omicron BA.1 or BA.5 S protein, to specifically boost antibodies recognizing viruses from the Omicron sub-lineage, have been designed for that reason. A study on one bivalent vaccine reported superiority in the induction of neutralizing antibodies to omicron sub-lineage variant BA.1 compared to the previously approved monovalent vaccine . AlthougWe now know that sterile immunity to SARS-CoV-2 infection is not achieved by vaccination, and that SARS-CoV-2 continues to circulate among humans. However, booster vaccinations remain important to prevent severe disease, especially in immunocompromised risk groups and the elderly. The willingness to receive regular booster doses in the general population is declining, partly because of the reduced disease severity observed after the emergence of the Omicron sub-lineages. Therefore, questions have arisen about future vaccination policies. Over 70% of the European adult population has completed the basic series of COVID-19 vaccination, yet just over 50% has received an additional booster dose . To deteSWITCH ON is a multi-center, open labelled, randomized, controlled trial. A total of 400 participants, between 18 and 65 years old, will be recruited from healthcare workers across four university medical centers (UMC) in the Netherlands . Participants will be predominantly, but not exclusively, recruited from previously published SWITCH , 18–20 avia questionnaires and retrospective assessment of N-specific antibodies in serum collected 3 months after booster vaccination. To measure vaccine immunogenicity, SARS-CoV-2 specific antibody and T-cell responses will be measured in all participants at day 0, 7 and 28, and 3 months after booster administration. Neutralizing antibodies against variants encoded by the vaccine , and circulating variants (e.g. Omicron BQ.1.1 and XBB) will be measured by an in-house developed plaque reduction neutralization test (PRNT) in a random selection of participants. The PRNT has been extensively validated but is RUO as there is no comparable IVD registered alternative. SARS-CoV-2-specific T-cell responses will be assessed via two assays (1): a CE-IVD whole-blood interferon gamma release assay  on all participants, and (2) a RUO activation induced marker (AIM) flow cytometry assay. This assay will use overlapping peptide pools from the ancestral S protein, and the Omicron BA.1, and BA.5 S proteins to stimulate peripheral blood mononuclear cells (PBMCs) isolated from 25% of participants in each branch of the trial arms. Cryopreserved PBMCs will additionally be used for the quantification and phenotyping of virus-specific B-cells, by staining with the ancestral, BA.1, or BA.5 S protein. The data will be analyzed on an intention-to-treat basis.Participants will be equally divided into two study arms: direct boost (DB) or postponed boost (PPB). The DB arm consists of two branches: one with 100 Ad26.COV2.S-primed participants and the other with 100 mRNA-based-primed participants. The PPB arm has the same structure Figure 1The primary outcome is defined as the fold-change in SARS-CoV-2-specific binding antibodies between day 0 and 28 for the adenovirus-primed and mRNA-based-primed participants, measured by quantitative IgG assay with the ancestral and Omicron BA.1 S protein. The secondary outcome focuses on recall responses induced by booster vaccination. To this end, S-specific antibodies and T-cells will be measured and compared on day 7 and 28 post boost. Clinical trials involving bivalent vaccines thus far only measured neutralizing antibodies at day 28 after the booster , 22. TheThe COVID-19 pandemic is currently in a transition phase towards endemic circulation, with reduced morbidity and mortality at the population level compared to the initial waves of circulation. Given the growing societal aversion towards repeated booster vaccinations, an important question is whether, and for how long, time-intervals between subsequent booster vaccinations can be prolonged. Differences in recall responses depending on the initial priming schedule (mRNA-based or vector-based) can guide the direction of future booster strategies, whereas the speed and breath of recall cellular memory after booster vaccination will provide important information for the timing of future booster vaccinations. The impact of intercurrent COVID-19 infections despite earlier vaccinations needs to be factored in when assessing these immune responses.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by METC Erasmus MC. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.All authors were involved in the design and execution of the study and writing of the manuscript. All authors contributed to the article and approved the submitted version.The trial is funded by Netherlands Organization for Health Research and Development ZonMw in the COVID-19 Vaccine program (project grant number: 10430072110001).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.


IntroductionHigher federal research funding levels may improve patient outcomes. We examined this relationship between traumatic brain injury (TBI) funding and all-cause in-hospital TBI-related mortality.MethodsUsing an ecological series analysis, we examined the linear trend in both clinical TBI research funding in year 2000 United States dollars ($)  and in-hospital isolated TBI mortality among patients aged 15 and older  between 2007-2015 with data from centers contributing all years of data for the study period. Linear regression was used to assess the relationship between mortality rate and total funding, lagged one to three years, both overall and within ten-year age groups.ResultsThe mean annual NIH-TBI research funding was $64.36 million . 192,597 encounters of patients 15 years and older, predominantly male (67.5%) and with polytrauma (59.9%), were included. There was no statistically significant reduction in in-hospital TBI-related mortality (14.15% in 2007 to 13.36% in 2015) for the cohort overall, but the mortality rate decreased for patients over 55 years. The greatest mortality reduction occurred in patients 85 years and older , followed by patients 75-84 years , patients 65-74 years , and patients 55-64 years of age . During the study period, annual NIH funding for TBI varied from the lowest level of $48.79 million (in 2007) to the highest level of $77.34.43 million (in 2005). There was no association between funding in the previous three years and the in-hospital TBI-related mortality rate.ConclusionThis study found a variable pattern in NIH funding for clinical TBI research and a contemporaneous reduction in moderate-severe TBI-related deaths only for those aged 55 years and older, but no association between funding and mortality. Traumatic brain injury (TBI) is a major cause of global death and disability, and in the U.S. alone, TBI contributes to about 30% of all injury deaths . In 2014The National Institutes of Health (NIH), under the oversight of the Congress, uses the burden of disease as the most important factor in making decisions regarding funding allocations. Other possible funding considerations include recent changes in the burden of disease, the potential for a scientific breakthrough and advocacy by disease-focused organizations. NIH funding has increased more slowly than growth in the gross domestic product in recent years. Hence, the rationale for NIH allocations for specific diseases is critical .The United States has a large TBI research portfolio, but the survival impact of federally funded research on patient outcomes is not well understood. One study analyzed the allocation of global investments from public and philanthropic funders for blast injury-related research and blast TBI between 2000 and 2019. While the authors concluded that blast TBI research received 42.6% ($384..3 million) of all blast-injury-related research [Human subjects approvalSince this work was considered non-human subjects research, this work was deemed to be exempt by the University of Washington Institutional Review Board . Study designThis was a retrospective, ecological time-series analysis examining the relationship between all-cause in-hospital mortality among isolated TBI patients and NIH funding within the prior three years in the U.S., as well as their individual trends over time.ExposureThe main exposure of interest was NIH funding for TBI research, adjusted to year 2000 United States dollars ($), data extracted from NIH. The NIH RePORTER  was querOutcomeThe primary outcome of interest was in-hospital mortality among patients with moderate-severe isolated TBI injuries as captured in the National Trauma Data Bank (NTDB) discharge disposition variable. Patients who died in the hospital or who were transferred to hospice were included in the mortality rate. Mortality was measured as the rate of in-hospital deaths per 10,000 isolated TBI hospitalizations. Data from patients hospitalized with TBI were extracted from the NTDB from 2007 to 2015. Since calculated abbreviated injury scores were not included in the NTDB database after 2015, we restricted our study period to 2007-2015, when data were available. Participating trauma centers from across the United States voluntarily submit their trauma data to the NTDB to improve trauma research. Isolated TBI encounters within NTDB were defined using the following criteria: TBI-related ICD-9 or ICD-10 code , 39.8% were transferred from referral facility, and 59.9% had polytrauma, meaning they had a documented AIS score for another body region other than the head that was less than or equal to 2. Patients had a median intensive care unit (ICU) length of stay of 4.4, interquartile range (IQR) of 1-5 days and a median hospital length of stay of 8.3, IQR of 3-10 days. Overall, 169,353 (59.4%) had a good discharge outcome, and 39,506 (13.8%) patients either died or were discharged to hospice. As shown in Figure NIH funding for clinical TBI research 2007-2015During the study period, annual NIH funding for TBI varied from the lowest level of $48.79 million (in 2007) to the highest level of $77.34.43 million (in 2005), and funding estimates adjusted using the gross domestic product (GDP)-based annual implicit price deflation from the year 2000  or by ten-year age groups Table . In this study, we examined trends in and the relationship between NIH funding for clinical TBI research three years prior and all-cause in-hospital TBI mortality in the U.S between 2007-2015. The main findings are 1) NIH funding for clinical TBI research fluctuated over the eight-year study period, 2) overall all-cause in-hospital TBI mortality did not decrease, and 3) when stratified by age group, in-hospital mortality decreased only amongst patients older than 55 years; most pronounced in the >85-year age group. There was no statistical indication of an overall relationship between all-cause in-hospital TBI mortality and funding in the previous three years, indicating the need for efforts beyond NIH funding to achieve timely improvements for all TBI patients.The study finds a reduction in all-cause in-hospital TBI mortality between 2007-2015 only for patients >55 years of age. Upstream, this variability may be due to known differences in mechanism, physiology and pathophysiology , resultsOur methodology in extracting NIH funding merits discussion. Examining the NIH RePORTER database, we used search terms that solely indicated clinical research funding and not pre-clinical research because it is more likely that the conduct of clinical or patient-oriented TBI research would more efficiently translate to changes in TBI care that improves TBI outcomes. Associating TBI NIH funding allocation with patient-level outcomes is appealing because it reflects a need to evaluate the impact of peer-reviewed research. However, these are notable limitations. First is the issue of NIH’s allocation pool not being mutually exclusive to TBI research only in that a research project may overlap two or more disease categories and disease severity (mild vs. moderate vs. moderate-severe) and hence may misrepresent its weight in terms of funding allocation. Second, NIH’s Research, Condition, and Disease Categories (RCDC) stratifies research funding allocation according to disease burden. In this case, funding for “all accidental injuries” from 2007 to 2015 shows a linear, year-on-year increase  [The lack of observed statistical association between funding and improvements in mortality observed at the ecological level does not mean that more granular benefits at the faculty level have not occurred. For example, a large-scale review of the UK’s National Institute for Health Research (NIHR) and Comprehensive Clinical Research Network (CCRN) reviewed an annual allocation of £285M and 2.3 million hospital admissions. They showed that institutions with higher research funding had lower mortality outcomes for emergency admissions than institutions with lower research funding . Study oThere are some additional study limitations and strengths beyond the important point that our study is ecological. Limitations are inherent limitations of the data sources; the NIH RePORTER database is drawn from several databases but does not encompass all federally funded research; hence we may have missed potential funding sources. There is also the possibility of under or over-reporting of funds towards TBI as NIH RePORTER allocations are not mutually exclusive between multiple projects. Regarding the NTDB database, weakness pertains to it being an administrative, subjective, self-reporting database, not primarily for research leading to inconsistent reporting, human error, and other biases. The NTDB represents a national sample of hospitals that choose to report their data to the NTDB, and thus the data are not nationally representative, and it is possible that centers that do not choose to report to the NTDB may experience different results than observed in this study. We only included data from trauma centers that reported to NTDB in all nine years were included in the study, which further limited the sample size. We also cannot comment on increased proficiency in TBI care of the elderly, which may influence the reduction in mortality numbers. We could not distill research relevant to more upstream TBI care than the hospital setting, such as the emergency department or clinic, but assumed that improvements in preadmission health care settings could improve hospital survival. We could not attribute research location or research topic to our observation of associated improved hospital discharge survival for patients hospitalized with TBI but assumed that all patients hospitalized with TBI are at risk of deterioration across hospital settings. The main strength is the novel use of publicly available data, both NIH RePORTER and NTDB, to understand the impact of research on clinical outcomes in TBI. These data also likely reflect death related to TBI and not polytrauma as we excluded patients with AIS scores greater than 2 in body regions other than the head. These findings add to our understanding of elderly patient outcomes in TBI over a recent eight-year period. This study finds a variable pattern in NIH funding for clinical TBI research and a contemporaneous reduction in moderate-severe TBI-related deaths for those only aged 55 years and older, but no association between in-hospital TBI-related mortality rate and funding in the prior three years. This study is a first attempt to understand whether national-level clinical research funding translates to timely patient benefit in TBI.


BackgroundElective orthopedic surgery, as well as the procedures of many surgical departments, have been severely curtailed by coronavirus disease 2019. Here, we aimed to analyze how all surgeons could safely perform essential procedures during the coronavirus disease 2019 pandemic.MethodsA retrospective review of elective surgeries performed between May 15, 2020, and February 28, 2022, was conducted. A screening questionnaire was used, and reverse transcription-polymerase chain reaction testing was assessed in all admitted surgical department patients. Their positivity rate and the positivity rate in our fever outpatient clinic were analyzed.ResultsOf 6099 patients who tested for severe acute respiratory syndrome coronavirus-2 during the study period, eight (0.13%) tested positive. The positive results were seen in four patients undergoing orthopedic surgery, two undergoing respiratory surgery, one undergoing breast surgery, and one undergoing plastic surgery. The number of patients who visited the outpatient clinic for fever was 15,639, including 1640 positive cases (positive rate of 10.5%). The positive rate of preoperative reverse transcription-polymerase chain reaction testing for scheduled surgery was consistently low and did not coincide with the peak of the wave of infection, while the positivity rate of outpatients with fever demonstrated a wave consistent with the national infection situation. All 6091 patients, excluding the eight positive patients, underwent surgery; all patients who underwent surgery were discharged from the hospital without developing coronavirus disease 2019 symptoms.ConclusionsOur findings suggest that the establishment of a universal reverse transcription-polymerase chain reaction testing system is essential for the safe performance of scheduled surgeries during the coronavirus disease 2019 pandemic. The rapid spread of coronavirus disease 2019 (COVID-19) led to it being declared a pandemic [As the virus continues to mutate and further waves of infection are anticipated, countermeasures based on sufficient verification are necessary for orthopedic surgery to be performed safely. The number of orthopedic surgeries in our department has remained almost the same before and during the COVID-19 pandemic: 1466 in 2019, 1464 in 2020, and 1474 in 2021. This means that orthopedic surgery was necessary even during the COVID-19 pandemic; thus, surgeons are required to take sufficient countermeasures against COVID-19 and establish a system to safely perform surgery. Our hospital comprises 11 surgical departments, including orthopedics, digestive surgery, respiratory surgery, breast surgery, neurosurgery, obstetrics and gynecology, urology, plastic surgery, ophthalmology, dermatology, and dental surgery. All surgical departments are required to have a system in place to safely perform scheduled surgeries during the COVID-19 pandemic, not just orthopedics. Although there is little evidence regarding universal testing using reverse transcription-polymerase chain reaction (RT-PCR) for elective surgery in Japan, there are several reports from other countries [The purpose of the present study was to report the percentage of positive RT-PCR tests for SARS-CoV-2 detected upon admission for elective surgery during the COVID-19 pandemic. We aimed to determine how all surgeons could safely perform essential procedures during the COVID-19 pandemic.This retrospective observational study was conducted at a secondary care hospital in a city with a population of approximately 200,000. It was conducted in accordance with the principles laid down in the Declaration of Helsinki and following institutional review board approval . In this study, a comprehensive agreement for academic use of the information such as type of treatments, treatment progress, or any other data acquired during their treatments was obtained from the patients by the hospital at the time of their hospitalization, and no identifiable information of the participants is included in the manuscript. In total, 6099 consecutive patients undergoing elective surgery between May 15 and February 28, 2022, were included in the study. Information regarding travel, occupation, contact, and cluster (TOCC) risk factors were documented for each patient. Screening for COVID-19 symptoms  was conducted, and the results were documented. If patients presented with any positive TOCC risk factors and/or exhibited symptoms, they were referred to a COVID-19 outpatient clinic. Thus, none of the included patients exhibited TOCC risk factors or COVID-19 symptoms.RT-PCR testing was performed for all patients prior to scheduled surgery using samples taken from the nasopharynx 3-5 days prior to admission. The RT-PCR assays were performed using LightMix Modular SARS and Wuhan CoV E-gene/ Wuhan CoV N-gene . We chose this kit because its sensitivity and specificity are 100%, and we can expect a stable supply.Due to the widespread of the COVID-19 in Japan, we believe that travel history is not a contributing factor and have removed travel history from the screening questionnaire after October 21, 2020 .The hospital maintained a no visitor policy throughout the study period. At the fever outpatient clinic, COVID-19 antigen and RT-PCR tests were performed; if either test was positive, the patient was considered to be infected with COVID-19. In the fever outpatient clinic, the COVID-19 antigen assay kit used the Elecsys SARS-CoV-2 Antigen , while the COVID-19 PCR assay kit used the Film Arrey Respiratory Panel 2.1  and Xpert Xpress SARS-Cov-2 Cepheid  for diagnosis.The positivity rates for scheduled surgical procedures and in the fever outpatient clinic were analyzed, and statistical analyses were performed using Excel statistics software ; data are represented as percentages.As shown in Table In total, 6091 patients (the eight patients with positive results were excluded) underwent surgery; all patients who underwent surgery were discharged from the hospital without developing COVID-19 symptoms. Conversely, the number of patients who visited the outpatient clinic for fever was 15,639, including 1640 positive cases (positivity rate of 10.5%). Figure Our study revealed a COVID-19 incidence rate of 0.13% among the 6099 patients tested for SARS-CoV-2 during the study period. Among patients for scheduled surgery, eight tested positive between May 15 and February 28, 2022, using routine nasopharyngeal RT-PCR testing. These eight patients exhibited no COVID-19 symptoms.It is possible that some patients who underwent surgery may have false-negative COVID-19 results. Therefore, the policy was to perform RT-PCR testing even after surgery if COVID-19 symptoms appeared.The most important finding was that the positivity rate of preoperative RT-PCR testing for scheduled surgery was consistently low and did not coincide with the peak of national infection. The low positive rate may be due to the fact that patients who were scheduled to undergo surgery were supported to pay attention to hand hygiene, wear masks, and maintain social distance, and the patients also followed these guidelines. RT-PCR testing should be performed regardless of the peak of infection since it is possible that preoperative RT-PCR shows false-negative COVID-19 results.Gruskay et al. reported that according to tests performed using preoperative nasopharyngeal swabs for COVID-19, 12.1% of patients were positive . ContrasSan Miguel County, Colorado, reported that SARS CoV-2 IgG antibody tests were performed county-wide in March and April 2020. Twenty-nine of 5455 tested individuals (0.53%) were IgG positive, and 79 (1.45%) were borderline . Our resThe American College of Surgeons recommends that elective surgery be considered essential. Maintaining access to surgery is an essential part of quality patient care, whether the surgery is needed to cure a medical condition, address infirmity, extend life, or contribute to patient well-being -9. In ouAs the American College of Surgeons recommends that "decisions to adjust surgical services up or down should occur at a local level driven by hospital leaders including surgeons and in consultation with state government leaders; the decisions should be based on local case incidence, ongoing testing of staff and patients, aggressive use of appropriate personal protective equipment (PPE), and physical distancing practices", we advocate that elective surgery be performed after universal preoperative RT-PCR testing during the COVID-19 pandemic -9.Our study has one notable limitation: it was conducted at a secondary emergency hospital located in a city with a population of approximately 200,000, thereby increasing the probability of selection bias. However, we can confidently assert that universal testing should be conducted.This study underscores the need for isolation of COVID-19 patients and their close contacts in the hospital. Thus, the identification of infected individuals is vital to prevent the spread of illness to other hospital personnel and patients. In conclusion, our findings suggest that the establishment of a universal reverse transcription-polymerase chain reaction testing system is essential for the safe performance of scheduled surgeries during the COVID-19 pandemic.


Mycobacterium tuberculosis (Mtb) genotyping. However, different optimized VNTR loci sets for improving the discrimination of specific Mtb genotypes have been proposed. In this regard, we investigated the efficacy of accumulation of the percentage differences (APDs) compared with the least absolute shrinkage and selection operator (LASSO) regression strategy to identify a customized genotype-specific VNTR loci set which provides a resolution comparable to 24-loci MIRU-VNTR in divergent Mtb populations. We utilized Spoligotyping and 24-loci MIRU-VNTR typing for genotyping 306 Mtb isolates. The APD and LASSO regression approaches were used to identify a customized VNTR set in our studied isolates. Besides, the Hunter-Gaston discriminatory index (HGDI), sensitivity, and specificity of each selected loci set were calculated based on both strategies. The selected loci based on LASSO regression compared with APD-based loci showed a better discriminatory power for identifying all studied genotypes except for T genotype, which APD-based loci showed promising discriminative power. Our findings suggested the LASSO regression rather than the APD approach is more effective in the determination of possible discriminative VNTR loci set to precise discrimination of our studied Mtb population and may be beneficial to be used in finding reduced number loci sets in other Mtb genotypes or sublineages. Moreover, we proposed customized genotype-specific MIRU-VNTR loci sets based on the LASSO regression and APD approaches for precise Mtb strains identification. As the proposed VNTR sets offered a comparable discriminatory power to the standard 24 MIRU-VNTR loci set could be promising alternatives to the standard genotyping for using in resource-limited settings.The 24-loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) genotyping has been used as an international standard method for  Mycobacterium tuberculosis (Mtb), as one of the deadly infectious agents, is imperative for epidemiological and biological purposes. Molecular typing methods play an important role in achieving this purpose and provide powerful tools to measure local and global tuberculosis (TB) surveillance  according to the manufacturer’s instructions and was used for the 24-loci MIRU-VNTR genotyping method as described previously  was used for analyzing all Mtb genotypes were initially identified with the MIRU-VNTR technique and confirmed with the Spoligotyping method. The MIRU-VNTR and Spoligotyping data were analyzed by the MIRU-VNTRplus web server1 and SITVIT-WEB online tool2  score, each locus showed a high (h > 0.6), moderate (0.3 ≤ h ≤ 0.6), and poor (h < 0.3) discriminative power  algorithm. LASSO regression method was used to provide a reduced, and hence, more cost-effective set of loci that could predict the Mtb genotypes with reasonable accuracy. The LASSO regression model, which is acknowledged to be suitable for high dimensional data regression analysis . Sensitivity evaluates model performance and measures a model’s capability to identify positive examples correctly. When sensitivity is used to evaluate model performance, it is often compared to specificity. Specificity measures the proportion of true negatives that the model correctly identifies. We assessed internal and external validity to validate the performance of LASSO regression. The fivefold cross-validation (CV) was used for evaluating internal validity. This approach randomly divides the data 5 times as training and test samples and runs the analysis on each fold. Then the sensitivity and specificity indices were calculated. External validity was tested by defining our dataset as a train set and an additional source of data as a test set, including the collection of 225 strains with their 24 MIRU-VNTR loci and genotype assignments provided from the MIRU-VNTRplus reference database (see text footnote 1) and a part of data from two previous studies . Then thTo APD calculation in each VNTR locus, firstly, we categorized our MIRU-VNTR data into eight data groups, including Beijing and Non-Beijing, CAS and Non-CA, NEW-1 and Non-NEW-1, Haarlem and Non-Haarlem, Cameroon and Non- Cameroon, LAM and Non-LAM, T and Non-T, and Ural1 and Non-Ural1. Then, the frequency of repeat numbers (patterns) at any VNTR locus was determined in both groups of each category. Finally, the APD value for each VNTR locus in every category was calculated as follows:Where s is the total number of distinct repeat patterns, Aj (Bj) is the percentage of A (B) category strains with the jth repeat pattern from all the strains of the A (B) category.According to results of the standard 24-loci MIRU-VNTR genotyping with TBminer database, we identified eight genotypes as follows: 101 CAS1-Delhi (33.00%), 88 NEW-1 (28.76%), 56 Beijing (18.30%), followed by 16 isolates as Haarlem (5.22%), 16 isolates as Cameroon (5.22%), 12 isolates as T (3.92%), 9 isolates as Ural1 (2.94%), and 8 isolates as LAM genotype (2.61%). The Spoligotyping method showed a similar result to MIRU-VNTR data . HGDI ofMtb population. Besides, HGDI, sensitivity, and specificity of each selected loci set were investigated based on the strategies. As shown in Mtb genotypes) compared with those based on the APD approach except for T genotype, which APD-based loci showed the better result. Besides, external and internal validity results for the LASSO regression approach showed proper and comparable sensitivity and specificity in most of the studied genotypes (We previously defined a combination of loci for specific genotypes (NEW-1 and CAS1-Delhi) based on APD . Here, wenotypes .In the CAS-Delhi population, a combination of five VNTR loci  was found as a proper set based on the descending order of the APD values . AccordiThe VNTR loci set obtained based on LASSO regression showed the similar level of discrimination as the 24 loci reference method (HGDI: 0.956). Besides, the estimated sensitivity and specificity of the selected loci set based on LASSO regression were more significant compared with the APD results .In the NEW-1 population, the VNTR loci set of ETRB (2461), MIRU10 (960), MTUB34 (3171), MTUB04 (424), and ETRA (2165) were identified based on the APD approach. The APD value of the selected loci was more than 59% . Based oIn the Beijing population, as shown in As depicted in Mtb genotyping. However, regarding a specific strain background and polymorphism which can affect the resolution of discrimination, various studies in the different geographical regions have tried to explore optimized VNTR sets for improving the standard typing method and offered different VNTRs combinations , MIRU16 (1644), MIRU26 (2996), MIRU27 (3007), MIRU31 (3192), MIRU39 (4348), MIRU40 (802), MTUB21 (1955), and QUB26 (4052) are more discriminative in the standard 24 MIRU-VNTR loci panel for identification of different  in Iran . However in Iran .We have previously reported that using the APD approach may facilitate efficient discrimination and clustering of NEW-1 and CAS populations . In the In the NEW-1 population, as a member of the Euro-American super lineage, five combinations of VNTR loci based on APD and five combinations of VNTR loci based on LASSO were found with a high capacity for efficient discrimination. In addition, a combination of VNTR MIRU10 (960), ETRB (2461), and MTUB34 (3171) which were similar between the two methods could be used a primary set for identifying the NEW-1 family. The efficient implementation of these methods for genotype data is helpful for the effective selection of VNTR loci for NEW-1 discrimination. However, based on the specificity of each selected set, we can suggest that using LASSO may be more effective than APD for discrimination of the NEW-1 population.In Beijing population, as the third dominant genotype, a set of loci, which can more effectively classify this genotype were obtained based on the LASSO method, including VNTR MTUB21 (1955), QUB11B (2163b), ETRA (2165), MTUB30 (2401), and MIRU31 (3192). . Five loci set selected based on APD method also showed the high discriminatory power in this genotype . In a previous study, 12 optimized loci were suggested for discrimination of Beijing genotype based on the combined PCA and HGDI methods. Among these loci, only five loci  were selected based on the PCA result . A diffeMtb genotypes and some genotypes in our study with small sample size like T. Another limitation of this study is that selection of VNTR loci was based on the predefined panel for standard 24 loci MIRU-VNTR typing, so evaluating additional loci could be beneficial to improve the efficiency of the selected customized loci set in discrimination of Mtb isolates in different settings. In addition, more Mtb genotypes should have been included in the current study.Other genotypes identified in our study were a part of the Euro-American super lineage, which is the most widely dispersed lineage. Different customized VNTR loci sets were offered based on both applied approaches to high effective discrimination of these groups. However, the selected loci sets based on both methods were reliable and promising in most of these genotypes, based on HGDI value, LASSO-based VNTR loci were more discriminative than the APD-based loci. Besides, no relevant study was found on the discriminative power of the loci combination based on APD, LASSO, and/or other statistical methods for Haarlem, Cameroon, LAM, and Ural1. Further investigations are crucial to accredit the efficiency of our implemented approaches in selecting discriminative loci in the other main Mtb strains identification. As the proposed VNTR set offered a comparable discriminatory power to the standard 24 MIRU-VNTR loci set could be promising alternatives to the 24-loci MIRU–VNTR genotyping for using in resource-limited-settings. Moreover, our findings suggested the LASSO regression rather than the APD approach is more effective in the determination of possible discriminative VNTR loci set to precise discrimination of our studied Mtb population and may be beneficial to be used in finding reduced number loci set in other Mtb genotypes or sublineages.In summary, we proposed customized genotype-specific MIRU-VNTR loci sets based on the LASSO regression and APD approaches for precise The original contributions presented in this study are included in the article/The studies involving human participants were reviewed and approved by Pasteur Institute of Iran. The patients/participants provided their written informed consent to participate in this study.SH and FV wrote the manuscript. FV supervised the project. FV, SDS, and AF designed the project. SH, NE, and MKK performed laboratory work. SE, MN, and MAKK performed the statistical analysis. All authors have read and approved the final manuscript.


The ongoing COVID-19 pandemic is among the worst in recent history, resulting in excess of 520,000,000 cases and 6,200,000 deaths worldwide. The United States (U.S.) has recently surpassed 1,000,000 deaths. Individuals who are elderly and/or immunocompromised are the most susceptible to serious sequelae. Rising sentiment often implicates younger, less-vulnerable populations as primary introducers of COVID-19 to communities, particularly around colleges and universities. Adjusting for more than 32 key socio-demographic, economic, and epidemiologic variables, we (1) implemented regressions to determine the overall community-level, age-adjusted COVID-19 case and mortality rate within each American county, and (2) performed a subgroup analysis among a sample of U.S. colleges and universities to identify any significant preliminary mitigation measures implemented during the fall 2020 semester. From January 1, 2020 through March 31, 2021, a total of 22,385,335 cases and 374,130 deaths were reported to the CDC. Overall, counties with increasing numbers of university enrollment showed significantly lower case rates and marginal decreases in mortality rates. County-level population demographics, and not university level mitigation measures, were the most significant predictor of adjusted COVID-19 case rates. Contrary to common sentiment, our findings demonstrate that counties with high university enrollments may be more adherent to public safety measures and vaccinations, likely contributing to safer communities. Many public health experts warned during the summer of 2020 that reopening campuses before vaccines were widely available was risky, and subsequent outbreaks among students, staff, and faculty within weeks of arriving on campus for the Fall semester quickly led to shutdowns3, questions remain about which strategies were most effective in lowering incidence of COVID-19 on campuses, and how campuses impacted the surrounding non-university communities. The overall sentiment, both in public opinion and some modeling studies, has been that college campuses fuel outbreaks and spread into the local community5. One study found that re-opening campuses to in-person instruction contributed to increased human mobility and was strongly associated with increased COVID-19 incidence in neighboring communities6. However, this study only analyzed teaching modality  and did not examine other mitigation and containment approaches that were implemented. Stratifying the analysis by collective COVID-response plan may reveal more information about the impact of these measures. In a study of a large , northeastern urban university with ample mitigation strategies (e.g. rapid delivery of SARS-CoV-2 polymerase chain reaction (PCR) test results, contact tracing, face mask use, reduced class size and density, and enhancement of all building air systems) more than half of cases were traced to a non-campus source, and no cases were attributed to classroom exposure7. These contradictions spawn a twofold question: are universities, particularly those with large  student populations, fueling community spread of COVID-19, and how?Due to the wide variation in the mitigation and containment strategies implemented during the Fall 2020 semester on college campuses across the U.S.9. A stochastic model by Gressman and Peck10 evaluating mitigation found that, in addition to high COVID-19 test specificity, remote instruction and a high capacity for student quarantine were critical to successfully managing outbreaks. Findings from an agent-based model also suggested that reducing direct contact in residence halls and classrooms through class size caps or hybrid options, combined with masking and social distancing, could keep the campus viral reproductive rate at or below 1.011. Additionally, evidence suggested that frequent testing and strict social distancing measures may prevent university shutdowns and the economic penalties associated with such a disruption, potentially outweighing the costs of implementing such surveillance12. However, given that providing masks, implementing remote learning, and conducting regular testing requires up front and ongoing funding that not all colleges and universities have, modification of these mitigation strategies is often needed 13.Observations of COVID-19 responses in the U.S. and other countries, and models of potential outcomes for the Fall semester demonstrated that a safe re-opening of university campuses depended on rigid adherence to containment  and mitigation strategies . A key component of this approach was frequent testing of students, faculty, and staff for COVID-19The aims of this investigation were twofold: (1) to estimate U.S. county-level COVID-19 case and mortality rates and compare those of counties with and without college campuses, and (2) to model the impact of mitigation efforts on case rates of COVID-19 in a sample of U.S. counties with college campuses. We hypothesized that colleges and universities with robust COVID-19 response plans  would have a protective effect both on campus members and their surrounding communities, and that overall, presence of universities would not negatively impact the overall surrounding community.14. We selected the time period of January 1, 2020 to March 30, 2021 to answer question one for three reasons: (1) the Spring (approximately January–May) and Fall (approximately September-December) periods capture the entirety of a typical university calendar year, providing a control period to adequately measure COVID-19 transmission in local communities, (2) The commencement of the fall semester  is a critical point as it is approximately the median time point for this analysis, and (3) The U.S. experienced three distinctive COVID-19 “waves” over this period, creating a large representative dataset for comparing counties with campuses across the country.SARS-CoV-2 laboratory-confirmed case and mortality data were acquired from the Centers for Disease Control and Prevention (CDC) data archiveEach case in this dataset contained 32 elements, including demographics  and county/state of residence. Numerous reporting agencies provide this information to the CDC and as a result, lineage-specific COVID-19 designation, symptom onset, and/or test positive dates were often incomplete, inconsistent, and/or provisional. All cases were aggregated with no sequencing-specific lineage designation. If multiple dates were listed, a single case-positive date was selected from the following (using the same order of preference as the CDC) data: symptom onset date, test positive date, and CDC report date. If no date or county of residence information was provided, the case was excluded. All personally identifiable information  were removed by the CDC prior to public release of the data. Geographic locations for each case were aggregated to county-level for additional privacy protections.15. Total enrollment by postsecondary institution for the Fall semester of 2018–2019 academic year was aggregated by county and divided into four categories. Counties with total enrollment x University enrollment (UE) data were acquired from the Integrated Postsecondary Education Data System (IPEDS)16. These data provide estimates of population by age from 60 months of sampling between January 1, 2015 and December 31, 2019. For purposes of this study, age groups have been categorized by 10-year intervals as 0–9, 10–19, 20–29, 30–39, 40–49, 50–59, 60–69, 70–79, and 80+ .County population was acquired from the American Community Survey (ACS) 2019 5-year estimate16, unemployment17, COVID-19 community vulnerability index (CCVI)18, percentage of population that was vaccinated as of March 30, 2021 (at least 1 dose)19, and percentage vote by party candidate in the 2020 U.S. Presidential Election20.Other factors of interest in evaluating COVID-19 among populations at the county level included median household income21. Only data from four-year universities were included in the analysis, and schools were organized by the enrollment size categories used in Aim 1. Reopening plan variables included the “Mode of Instruction” (MOI) as of September 1, 2020 and proposed on-campus COVID-19 testing strategy. Other institution factors (e.g. land grant university status and degree of campus urbanization)15 were included in the analysis due to potential impact of funding mechanisms and population density structures. Additionally, we evaluated county-aggregate factors such as self-reported masking adherence, state-instituted mask mandates22, median household income16 and unemployment rates17.Highly incongruous COVID-19 policies were implemented across U.S. universities during of the Fall 2020 semester reopening. In light of this, to address Aim 2 we selected aggregated variables collected by the College Crisis Initiative at Davidson College that could be compared widely across a sample of institutions of various size andAim 1: Cases and deaths were age-adjusted using the 2019 ACS 5-year estimates as the reference population. Each county’s COVID-19-confirmed cases and deaths were organized by age group for the time period between January 1, 2020 and March 30, 2021. These were then aggregated as a total for each outcome and age-adjusted.25.Age-adjusted COVID-19 case and death rates were evaluated across three time scenarios: (1) January 1, 2020 to March 30, 2021; (2) By each “wave” period, determined by natural breaks between peaks among national cases ; and (3) Before and during the Fall 2020 academic semester 26. Group means were compared using Student’s t-test or Dunnett’s Test (control group = counties without university enrollment). Comparisons were significant at p < 0.05. Age-adjusted case and mortality rates were modeled separately as dependent variables. Models were stratified by county university enrollment size, totaling eight standard least squares regression models. Final model selections were made using backwards Bayesian Information Criterion (BIC)-based stepwise regression. Overall significance of an independent variable was assessed by its frequency of inclusion in each of the four county university enrollment types, as well as averaging the logWorth ) of that variable across all four university county types.All statistical comparisons of groups for Aim 1 were assessed using JMP® (Version 16.0)FactomineR package27 in R (version 4.1.2) was conducted to identify important variables related to university reopening plans. Once the contributions of these variables to the overall variance of the dataset were assessed, a hierarchical cluster analysis was performed  to identify similar school mitigation strategy clusters associated with population-adjusted COVID-19 cases at the county level.Aim 2: Since the college reopening dataset contained both quantitative and qualitative variables, a factor analysis of mixed data using the MASS package28 to identify university COVID-19 mitigation strategies and other county-level variables that significantly predicted population-adjusted county COVID cases in the Fall 2020 semester. Model fit was evaluated with the performance package29 which gives a performance score based on the model’s BIC, Nagelkerke’s R2, and root-mean square error.Finally, due to overdispersion in the case data, we fit negative binomial models using the By March 30, 2021 a total of 22,385,335 cases and 374,130 deaths were reported to the CDC. Between January 1, 2020 and March 30, 2021, increasing county university enrollment was associated with significant reductions in COVID-19 case rates, but only slight differences in mortality rates  only explained 20% of the cumulative variance in population adjusted COVID-19 cases during the Fall of 2020 Table . Howeverp value ≤ 0.05) were retained. Clusters were most heavily defined by the school location setting , the county enrollment size, and the size category of the institution. Cluster 1 represented suburban and city-based small private institutions in counties with large student enrollments that did not report COVID measures for the Fall 2020 semester. Cluster 2 represented larger, city-based land grant public institutions that remained online or in hybrid instruction mode for the fall 2020 semester, and that offered multiple testing options for students. Schools in clusters 1 and 2 were in counties under mask mandates and that reported high mask usage. The third cluster was defined by small schools in counties with either no or small student enrollments, that held in-person instruction during the Fall of 2020, offered voluntary or no testing options for students, and whose counties reported low to moderate mask usage and had no mask mandates in place at the state level.From these factors, we constructed a hierarchical cluster analysis that identified three distinct school clusters Table  that werBest fit models that examined the association of campus COVID-19 mitigation strategies  and economic/county-level covariates  with population-adjusted cases in the Fall of 2020 showed that the most strongly contributive factors to increased county population-adjusted case numbers were low and moderate mask usage, lack of state mask mandates, and median household income Table . For theIt had been speculated that counties with large university enrollments were at higher risk for COVID outbreaks in the U.S. In this analysis, we evaluated a total of 22,385,335 cases reported to the CDC, representing 3,047 U.S. counties from January 1, 2020 through March 30, 2021. After all cases and deaths were aggregated to the county level and categorized by their total university enrollment sizes, this analysis found that the presence of large university enrollments was associated with lower county COVID-19 case rates.30 Second, although the 0–9 and 80+ year old age groups experienced the lowest case rates, the 80+ year old age group’s risk of death was substantially higher than all other age groups. These trends corroborate the widely observed findings pertaining to COVID-19 fatality32.A retrospective analysis evaluating 15 months of cases and deaths caused by COVID-19 reveals small, but significant reductions in cases among counties with increasing university enrollments. However, little to no change was noted with respect to mortality rates. Further analyses focused on differences between age groups also reveal little to no variation in the case and mortality rates of each group across university enrollment size. However, notable age-related trends were discovered. First, the highest case rates were among young to middle-aged adults (20–59), with 20–29-year-olds experiencing the highest case rates than any other age group—a finding also found by Monod et al.The time series plots of daily aggregated county averages of case and mortality rates Fig.  show obsThe second epidemiologic period of interest was among counties before and after the Fall 2020 semester. As seen in the wave analysis, all counties experienced a rapid increase in both COVID-19 cases and deaths after the start of the Fall 2020 semester. However, counties with increasing university enrollment experienced significantly lower case rates  compared to counties with no university enrollment. Counties with medium and large university enrollments also resulted in significantly lower death rates  compared to counties with low or no university enrollment.Our sub-group analysis of COVID-19 mitigation strategies for the Fall 2020 semester provide further evidence that colleges and universities were not associated with increases in county-level cases—even before cohesive containment plans were established. The cluster analysis identified that schools identified in Cluster 2 tended to be larger, land grant universities that maintained entirely online or hybrid course instruction during the Fall 2020 semester and were likely to be in counties with lower population-adjusted COVID cases. These schools were more likely to have mandatory student testing that was significantly associated with overall lower county cases numbers. During the Fall 2020 semester, county and state-level factors  were far more significantly predictive of overall county-level cases, which held true during the larger analysis period.Overall, the COVID-19 pandemic through March 30, 2021 rapidly spread through all U.S. counties with similar patterns in the timing and intensity of cases and deaths, regardless of the size of university enrollment. However, the magnitude by which cases and deaths affected counties is strongly associated with university enrollment. Although there were minimal differences among death rates by university enrollment, large enrollment universities were most affected by COVID-19 in the early stages of the pandemic—a suspected driving force behind the lack of significant differences in overall mortality rates. However, as the pandemic progressed in intensity (case and deaths per day), counties with increasing university enrollments experienced decreased risks in acquiring, and dying from, COVID-19.Together these two analyses strongly suggest that community-level variables—and not universities—are what drove COVID-19 cases during this time period. Despite having larger populations, counties with large university enrollments fared better than counties with little or no university enrollments, especially as COVID-19 cases surged through the winter of 2020–2021 (wave 3). In comparison to counties with little or no university enrollment, large university enrollment counties contained higher household incomes, less unemployment, and had higher vaccination rates (% with at least 1 dose). These counties also tended to enforce statewide mandates more frequently and for longer throughout the pandemic compared to counties with little to no university enrollments Tables  and S2.33. Using the 2020 U.S. Presidential election as a proxy for determining a county’s political affiliation, the associations of COVID-19 cases and deaths are moderately correlated . Counties without higher-education enrollments were also severely limited in this dataset, which could have impacted the analysis. We also assumed the mitigation plans to be static over the course of the Fall 2020 semester due to the lack of available data of changes. Given that this was the first semester with some schools in person, we felt it was likely that a university would maintain proposed plans, and if changes occurred, they would be to bolster mitigation, not reduce.This study incorporates key differences among American counties stratifying across a spectrum of enrolled university students. In general, counties with increasing enrollment populations tend to be more populated and urban. As such, several potentially important factors associated with COVID transmission, reporting, and knowledge, attitudes, and practices have been generalized or overlooked. Future studies would provide a great service to public health by expanding on the methodologies and results of this study on several of these key factors. For example, counties with large university enrollments appear to have many key protective factors in place to mitigate COVID-19. However, these counties also contain significantly larger populations of black, indigenous, and people of color (BIPOC) that suffer from disproportionate racial and health inequities. Consequently, social vulnerabilities are significantly higher in counties with large university enrollments. Preliminary analyses of this dataset, in respect to COVID-19 outcomes by race and ethnicity, suggest corroborative evidence of these inequities (data not shown). Future studies should also evaluate the co-evolution and/or competition between COVID-19 and other respiratory viruses, particularly seasonal influenza and respiratory syncytial virus conducted in a similar longitudinal analyses as this study.An increase in a county’s university enrollment is associated with a lower rate of COVID-19 cases and deaths compared to counties with no university enrollments.Counties with the largest universities tend to have greater population sizes, higher household income, lower unemployment, a higher percentage of people partially vaccinated against COVID-19, and a higher proportion of the population voting for Biden in the 2020 presidential election, but also a higher social vulnerability, than those with no university enrollment.Counties with university enrollments tend to have higher enforcement of statewide closing mandates than those without.Despite having high population densities and high social vulnerabilities, individuals in counties with large university enrollments had reduced COVID-19 case and mortality rates than those without university enrollments, especially in the third wave of the pandemic.Increasing education levels, enforcement of closing mandates, adherence to public health recommendations, and political affiliation were all associated with lower COVID-19 case and mortality rates.There was no significant impact on community cases from universities who returned for the Fall 2020 semester; county-level factors were the leading predictors of cases.These results offer evidence against the presumption that universities increase risk of COVID-19 community transmission.Supplementary Information.