Although the negative impact of smoking on health has been confirmed in various studies, few have explored psychological factors mediating the relationship between smoking and health-related quality of life (HRQOL). This study aimed to investigate the relationship between smoking and HRQOL in the Chinese population and the mediating role of negative emotions (NEs).Survey data were derived from a cross-sectional study conducted in China from 20 June to 31 August 2022. We recruited participants from 148 cities across the country using a stratified multistage sampling method. The HRQOL of the dependent variable was measured using the Chinese version of European Quality of Life-5 Dimensions (EQ-5D-5L). The Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Perceived Stress Scale (PSS-4) were used to measure NE parameters including depression, anxiety, and perceived stress, as the intermediate variables. A multiple parallel mediation model was used to analyze the mediating role of NEs in smoking and HRQOL.A total of 21916 valid questionnaires were collected, of which 3010 (13.7%) and 18906 (86.3%) were categorized into smokers and non-smokers, respectively. The HRQOL (EQ-VAS score) of smokers (71.70 ± 23.08) was lower than that of non-smokers (73.69 ± 21.32), whereas the depression and anxiety levels of smokers were higher than those of non-smokers . Moreover, smoking, NEs (depression and anxiety), and HRQOL showed pairwise correlations. According to the mediation analysis, depression  and anxiety  mediated the relationship between smoking and HRQOL after adjusting for demographic and life factors.These findings emphasize the necessity of studying the interaction between smoking, HRQOL, and Nes, and complementing the research on the impact of psychological factors on the HRQOL of smokers. Public health activities should focus on mental health and take targeted measures for the prevention, treatment, and rehabilitation of smokers. China is the largest producer and consumer of tobacco, consuming about 40% of the world’s tobacco; the total number of smokers in China exceeds 300 million, accounting for one-third of the world’s smoking population2. China’s economy, social order, and public health have suffered tremendously as a result of heavy tobacco consumption, with approximately one million deaths per year from tobacco-related diseases3.Tobacco use is one of the most serious public health problems worldwide. Smoking caused approximately 100 million deaths globally in the 20th century, mostly in low- and middle-income countries, including China4, a multidimensional evaluation index that includes physical health, psychological status, social relationships, and subjective satisfaction. It facilitates not only the comprehensive evaluation of an individual’s health status but also the policy legislation and health plan implementation for health institutions. Previous studies have shown a significant negative association between smoking and HRQOL, with non-smokers or former smokers having higher HRQOL scores than long-term smokers5. The association between smoking and HRQOL in terms of physical factors has been extensively examined, whereas the discussion surrounding psychological factors in this relationship has been comparatively limited. In addition, smoking is reported to have a stronger correlation with the mental health part than the physical health part of HRQOL5, possibly due to the worsening of negative emotions (NEs)6. Accordingly, it is of great significance to clarify the complex path relationship between the smoking and HRQOL.In addition to the direct harmful consequences to an individual’s survival, smoking also impacts health-related quality of life (HRQOL)7. These not only lead to increases in problematic behavior but are also important causes of emotional disorders8. Although NEs are often reported as factors that induce smoking, an interaction between these two parameters has also been observed9.NEs are subjective experiences of depression and unpleasantness that include various emotional states10. Further, the emotional states of depression, anxiety, and stress are closely related, together comprising NE11. Smoking is a reported risk factor for depression, anxiety, and stress. Compared to non-smokers, smokers have more serious symptoms of depression and anxiety12. Therefore, further studies are necessary to determine whether the components of NE mediate the relationship between smoking and HRQOL.NE is an important risk factor for HRQOL13. Furthermore, previous studies have only discussed the relationship between smoking and HRQOL in specific populations in terms of disease, lifestyle, and demographic factors15, but studies on the general population are lacking. In addition, most studies have just explored the effects of individual emotions, such as depression, on smoking and HRQOL16, and have not fully explored the overall impact of a group of NEs. Thus, the associations between smoking, NEs, and HRQOL should be investigated in the general Chinese population.Few studies have elaborated on the interaction between smoking and HRQOL in low- and middle-income countries. Although China is the world’s largest producer and consumer of tobacco, far fewer studies on the effects and mechanisms linking smoking and HRQOL have been published in China than those in Western countriesThis study aimed to investigate the association between smoking and HRQOL in the Chinese population and to determine the mediating role of NEs  using a multiple mediation model . Based ohttps://www.wjx.cn/) and shared with participants in face-to-face sessions.The data for this study were obtained from a cross-sectional survey of Chinese residents. The survey was conducted from 20 June to 31 August 2022 involving 23 provinces, 5 autonomous regions, and 4 municipalities in mainland China. In total, 148 cities were extracted using a random number table. From each province or autonomous region, we included the provincial capitals and 2–6 cities of different sizes. In total, 202 districts, 390 towns/streets, and 780 communities/villages were selected using stratified and quota sampling. Potential participants were contacted via phone or face-to-face by investigators. To ensure the effective implementation of the survey, investigators were publicly recruited in each city and strictly trained, including standardized processes and anticipating unforeseen circumstances, to respond to the survey. The online questionnaire was implemented using Wenjuanxing  age ≥12 years, 2) Chinese nationality, 3) Chinese residence , 4) voluntary participation in the study, with informed consent, 5) completion of the online questionnaire survey either alone or with the help of the trained investigators; and 6) comprehension of each item in the questionnaire. Exclusion criteria were: 1) participants who were diagnosed or self-reported with mental disorders, 2) cognitive impairment; and 3) participation in other similar research topics.Ethical approval was obtained from the Ethics Committee of Peking University. Before participation, the investigators clearly stated the purpose and content of the study. After obtaining informed consent, the participants were able to answer the questionnaire and had the right to withdraw their consent at any time. The data of all participants were anonymized for further analysis.Health17, which consists of two parts: a health questionnaire and utility conversion value. The health questionnaire consists of the EQ-5D descriptive system and the European Quality-Visual Analogue Scale (EQ-VAS). The EQ-5D descriptive system comprises five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression18. The EQ-VAS is a standard, vertical, 20 cm visual analogue scale. The scale ranges from 100  to 0 19. Cronbach’s coefficient for this scale in this study was 0.624.HRQOL in this study was measured using the Chinese version of European Quality of Life-5 Dimensions (EQ-5D-5L) questionnaire17. Therefore, this study used the EQ-VAS score as the dependent variable, which can directly obtain information on the subjective perception of a participant’s health status at that time.The intermediate variables in this study include anxiety and depression, partially overlapping with the five dimensions of the descriptive EQ-5D system. The EQ-5D health index converts the five-dimensional measurements into a single index value and uses it as a dependent variable. Although both the EQ-5D health index and EQ-VAS are measures of overall health, the former estimates the value of a respondent’s health from the perspective of the general public, whereas the latter takes the perspective of the respondentParticipants were asked: ‘Do you have a habit of smoking?’. Response options were: ‘yes’, ‘have quit smoking’ or ‘no’. Based on this question, smoking status was dummy-coded as: 1) smoking (participants who smoked); or 2) non-smoking (participants who had never smoked or had quit smoking).20 demonstrated that depression, anxiety and perceived stress combined, are associated with lower quality of life. To examine the magnitude of the mediating effects of depression, anxiety, and stress on NEs, the following three separate scales were used for testing.In a study of NEs and quality of life in Chinese adolescents, Geng et al.Perceived stress21 to measure an individual’s perceived stress, ability to cope with it, and related coping characteristics. It is rated on a 5-point Likert scale from 0 to 4 for each item, ranging from ‘never’ to ‘always’, with questions 1 and 4 being positively assigned and questions 2 and 3 being negatively assigned. A higher total score on the scale indicates a higher perception of stress. Cronbach’s α coefficient for this scale in this study was 0.826.The Perceived Stress Scale (PSS)-4 was developed by Cohen et al.Anxiety22, based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) diagnostic criteria in the United States. GAD-7 has seven items, each rated on a 4-point scale, from 0 to 3, with the total score being the main statistical indicator. A higher score corroborated with more severe anxiety. A total score of 0–4 indicates no clinically significant anxiety, 5–9 indicates mild anxiety, 10–14 indicates moderate anxiety, and ≥15 indicates severe anxiety. The maximum sensitivity and specificity were obtained when a score of 10 was obtained. Cronbach’s α coefficient for this scale in this study was 0.942.The Generalized Anxiety Disorder (GAD)-7 is a brief self-rating scale of anxiety symptoms developed by Spitzer et al.Depression23. In the present study, Cronbach’s α coefficient for this scale was 0.921.The Patient Health Questionnaire (PHQ)-9 is a brief and validated self-assessment scale of depressive status based on the nine items of the DSM-IV diagnostic criteria and is used to rate the severity of the respondent’s depressive status. It consists of nine items, with each item’s response consisting of four options: ‘not at all’, ‘a few days’, ‘more than half of the days’, and ‘almost every day’, with scores of 0, 1, 2, and 3, respectively. The maximum total score is 27. A total score of ≥5 on the assessment was considered positive, indicating the possible presence of depressive mood, with scores of 5–9 deemed likely to have mild depression, 10–14 likely to have moderate depression, and 15–27 likely to have severe depression14. The demographic characteristics included sex, age, residence , occupational status , education level , and monthly household income . Lifestyle factors incorporated drinking status  and the presence or absence of self-reported chronic conditions, including hypertension, coronary heart disease, and stroke.Factors potentially influencing HRQOL were identified from the literature24. Pearson’s correlation coefficient and the eta (η) coefficient were used to evaluate correlations between HRQOL, NEs , and smoking status.All statistical analyses were performed using IBM SPSS Statistics version 24 . All statistical tests were two tailed. Data normality was assessed using the Kolmogorov–Smirnov normality test. Statistical descriptive data included mean and standard deviation, and frequency and percentage. The t-test was used for continuous variables, and the chi-squared test or Kruskal–Wallis one-way ANOVA were used for categorical variables to compare the differences between smokers and non-smokers. In the subsequent hypothesis test, collinearity test results were first used to ensure that the expansion factor of the variable did not exceed 10, indicating no collinearity between variables. Moreover, the Harman single-factor test was used to assess the common method bias. The results showed that the first factor without rotation was 35.8%, which is less than the standard boundary value of 40%, suggesting no serious common method bias25. The relative mediating effect was further tested by bootstrap repeated sampling using the PROCESS macro of SPSS. The bootstrap test resamples the population data with replacements for the same number of n data points, and this procedure is repeated for k samples. The recommended sampling size is k=5000. Bias-corrected and accelerated bootstrap confidence intervals (95% BCa CIs) were used to correct for bias and skewness. It was considered statistically significant if the confidence interval did not include the value 0 for the indirect effect of smoking on HRQOL16. Finally, we obtained the total, direct, and indirect mediating effects of each variable. We established five equations to estimate the impact of smoking on HRQOL:We used a multiple parallel mediation model to assess the effect of smoking (binary variable) on HRQOL (continuous variable), and the mediating role of NE (continuous variable). Because the independent variable was binary, the relative mediation analysis method proposed by Hayes and Preacher was usedY = i + cX + eM1= i M1+ a1X + eM1M2= i M2+ a2X + eM2M3= i M3+ a3X + eM3Y = iY + c’X + b1M1+ b2M2+ b3M3+ eYY represents HRQOL, X smoking, M1 depression, M2 anxiety, M3 perceived stress, c the total effect of X on Y, c’ the direct effect of X on Y, ai the effect of X on Mi (i = 1 to 3), bi the total effect of Mi on Y (i = 1 to 3), I the intercept, and e the error.where Among the participants, 3010 (13.7%) were smokers and 18906 (86.3%) were non-smokers. The smokers had a significant sex bias, with the majority being men (90.1%). The mean age of smokers was 44.29 years, which was higher than that of all participants (39.43 years) and non-smokers . Compared to non-smokers, smokers had a significantly lower education level (p<0.001), with more than half having a lower secondary education level or less. In addition, compared to non-smokers, smokers were more inclined to be retired/unemployed and belong to rural populations and low-to middle-income households. Additionally, smoking was often accompanied by alcohol consumption and a high percentage of chronic diseases . In terms of NEs, smokers scored higher than non-smokers in all dimensions, with depression (p<0.001) and anxiety (p=0.002) being significantly different between the two groups. The mean EQ-VAS score for the total sample was 73.42, with smokers having a lower EQ-VAS score  than non-smokers (73.69). Overall, the health status of smokers differed from that of non-smokers.As smoking was a binary variable, the η coefficient was determined to analyze the correlations of smoking with HRQOL and NEs. Because HRQOL and NEs were continuous variables, Pearson’s correlation analysis was used.This study followed a four-step procedure to examine the mediating role of NEs on the association between smoking and HRQOL. The following condition was required: significant association between: 1) smoking and HRQOL, 2) smoking and NEs; 3) NEs and HRQOL; and 4) a significant indirect path coefficient of smoking influencing HRQOL through NEs. Satisfaction of the latter condition can be determined using the bias-corrected perceptual bootstrap method. As there was no significant association between stress and smoking  and 2, iThe settings of all regression models in the mediation analysis are shown in 26 agreed that smoking was associated with poor HQROL. The HRQOL of Chinese smokers was significantly lower than that of the general population, similar to the results of a previous national survey27. This may be because smokers experience obstacles in mental health, thereby affecting their subjective assessment of HRQOL, whereas ex-smokers or never smokers are superior regarding emotional and mental health28. Therefore, our study focused on HRQOL differences between smokers and non-smokers in China and the psychological mechanisms influencing HRQOL, which is of great significance in strengthening the social attention to the health of smokers and improvement of HRQOL in smokers.our knowledge, this is the first study focusing on psychological parameters involved in the relationship between smoking and HRQOL in the general Chinese population. In this national population-based study, we assessed the differences between smokers and non-smokers using descriptive statistics, and investigated the association between smoking and HRQOL, as well as the mediating role of NEs in this association. Smoking status, depression, anxiety, and HRQOL were correlated. Regression analysis showed that smoking was associated with higher depression and anxiety levels than not smoking, and higher depression and anxiety levels were associated with poorer HRQOL. The results of the mediating effect analysis indicated that smokers were affected more by anxiety and depression than non-smokers in terms of HRQOL. This verified hypothesis 1 that smoking is negatively correlated with HRQOL. Despite using different tools to measure HRQOL, previous surveys in different countries7. Because of long-term smoking, nicotine causes changes in neurotransmitters in the brain that affect mood29. Smoking can also lead to a disorder of the hypothalamus-pituitary-adrenal system and high levels of secreted cortisol, resulting in dysfunction of the neurobiological system, leading to depression and anxiety30. Although we also included perceived stress as an NE parameter in hypothesis 2, the results showed no significant correlation between smoking and stress. The relationship between smoking and stress remains controversial as some studies suggest that smoking is closely related to stress, whereas others suggest that there is no significant relationship between these factors31. Thus, the interaction mechanism between smoking and stress may be complex, and further longitudinal studies are needed to explore its causal relationship.Similar to the findings of previous studies, smoking was associated with higher levels of depression and anxiety32 and elderly33 populations have explained the association between mental disorders and low HRQOL, and these findings are consistent with the results of our current research. Our study provides new evidence for this relationship in a general population and in smokers in a national sample, and may help to better understand the psychological determinants of improving HRQOL.In the present study, depression and anxiety were associated with lower HRQOL. Previous studies in subgroups such as chronically ill16 where, after adjusting for depression scores, the association between smoking and HRQOL disappeared. This emphasizes that depression and anxiety play key roles in the relationship between smoking and HRQOL. Smoking cessation measures can effectively improve mental health, and mental healthcare may reduce the incidence or prevalence of smoking. However, additional investigations are required to establish the temporal association between mental health and smoking.Through bootstrap mediation analysis, we also partially verified hypothesis 2 proposed in this study that the NE factors depression and anxiety play an indirect role in the association between smoking and HRQOL. The results showed that smokers had higher levels of depression and anxiety than non-smokers, adversely affecting their HRQOL. Depression and anxiety, respectively, mediated 49.5% and 29.9% of the differences in smoking and health status. After adjusting for control variables and depression and anxiety scores, the direct link between smoking and HRQOL disappeared, indicating that depression and anxiety played a mediating role. This is similar to the findings reported by Milic et al.34, the feedback effect between variables leads to simultaneity bias, that is, the two-way causal problem. For example, although we propose that smoking predicts occurrence of NEs, people smoke to reduce their NEs35. Finally, although we adjusted for control variables in the study, there may still be unmeasured confounding factors (such as lifestyle and demographic variables). Thus, it cannot be determined if the observed or unobserved effects are related to the measured variables or the unobserved factors.This study has several limitations. First, it was based on cross-sectional data. The results can only demonstrate association but cannot establish a causal relationship. Prospective studies are needed to compare smoking status, NEs, and HRQOL. Second, smoking, stress, depression, anxiety, and HRQOL were measured by self-administered questionnaires, and the results may be affected by self-report and social expectation biases. Third, NEs mainly involve the study of depression, anxiety, and perceived stress, but there is a lack of awareness of other NEs, such as anger, loneliness, and panic. Future research should focus on including these emotions. Fourth, according to a question raised by Baron and KennyFirst, our results provide deeper insight into the relationship between smoking and HRQOL from a psychological perspective. From an academic point of view, we suggest that studies of substance abuse should be combined with those of mental health, which may help to provide additional insight for improving the health status of smokers. Second, future research needs to include large-scale longitudinal studies to determine the causal relationships between smoking, NEs, and HRQOL, to provide more information on internal connections. Third, from a practical point of view, we suggest that professionals, such as public health institutions, policymakers, and community personnel, pay more attention to the HRQOL of smokers and their psychological impact mechanism, to inform both smokers and non-smokers of the impact of smoking on HRQOL. In addition, when formulating health policies and carrying out smoking cessation campaigns, attention should be paid to smokers and people with high NE levels. Improvements in mental health and smoking prevention should be combined to create a healthier social environment. In addition, access to such information also has the potential to help smokers take proactive measures to improve their HRQOL.We found that HRQOL (EQ-VAS score) was significantly lower in smokers than in non-smokers in the Chinese population and that smoking was associated with higher NEs (depression and anxiety). According to the mediator effect analysis, depression and anxiety play key roles in the association between smoking and HRQOL. This suggests that smokers have higher levels of depression and anxiety than non-smokers, which leads to lower HRQOL. This finding reveals the relationship between NEs in smoking and HRQOL, emphasizes the role of mental health in smoking and HRQOL, and provides new perspectives for smoking cessation campaigns and HRQOL improvement for the Chinese smoking population.


Respiratory syncytial virus (RSV) is a common respiratory pathogen that causes mild cold-like symptoms and severe lower respiratory tract infections, causing hospitalizations in children, the elderly and immunocompromised individuals. Due to genetic variability, this virus causes life-threatening pneumonia and bronchiolitis in young infants. Thus, we examined 3600 whole genome sequences submitted to GISAID by 31 December 2022 to examine the genetic variability of RSV. While RSVA and RSVB coexist throughout RSV seasons, RSVA is more prevalent, fatal, and epidemic-prone in several countries, including the United States, the United Kingdom, Australia, and China. Additionally, the virus's attachment glycoprotein and fusion protein were highly mutated, with RSVA having higher Shannon entropy than RSVB. The genetic makeup of these viruses contributes significantly to their prevalence and epidemic potential. Several strain-specific SNPs co-occurred with specific haplotypes of RSVA and RSVB, followed by different haplotypes of the viruses. RSVA and RSVB have the highest linkage probability at loci T12844A/T3483C and G13959T/C2198T, respectively. The results indicate that specific haplotypes and SNPs may significantly affect their spread. Overall, this analysis presents a promising strategy for tracking the evolving epidemic situation and genetic variants of RSV, which could aid in developing effective control, prophylactic, and treatment strategies. In the first two years of life, 90% of infants are infected with RSV and at risk of reinfection at any moment. Lower respiratory infections occur in many RSV patients1. In children under five, the virus is the leading cause of acute lower respiratory tract disease (LRTI)2. About 40% of RSV infections in infants may result in LRTI, mostly pneumonia and bronchiolitis2. As a result, up to 199,000 pediatric fatalities, 3 million hospitalizations, and over 33 million LRTIs are all attributed to RSV worldwide1. In Canada, RSV causes 5800 to 12,000 hospitalizations annually, with a reported increase in bronchiolitis during the last two decades2. Between 1997 and 2000, RSV bronchiolitis accounted for an average of 77,700 yearly hospitalizations in the United States among babies less than one-year-old. The hospitalization rate for people in this age bracket rose 25% between 1997 and 20023.After being discovered in chimpanzees in 1955, the respiratory syncytial virus (RSV), an RNA virus of the Paramyxoviridae family and Pneumovirus genus, was shortly found to be a pathogen in humans2. Recent studies in China found 402, 288, and 415 confirmed cases of RSV infections over three consecutive years 4. Of the 8,461 confirmed cases of RSV in Denmark in 2022, another research found that 3,417 required emergency hospitalization5. However, preterm newborns, patients with underlying cardiac, pulmonary, neurologic, and immunological issues, and the elderly have a far more significant morbidity and mortality risk from this illness6. The RSV genome is a single-stranded, non-segmented molecule that is 15,191–15,226 nucleotides long and contains 10 functional genes (3′ NS1-NS2-N-P-M-SH-G-F-M2-L) [9]. Each mRNA typically encodes a single essential protein, except for M2, which includes two separate ORFs that slightly overlap and encode M2-1 and M2-2.RSV, like influenza viruses, has a seasonal epidemic, peaking between October and December in temperate countries and April and September in tropical and subtropical regions, but with milder symptoms1. Based on the genomic versatility, the virus only has one serotype, but it is further subdivided into two strains, RSVA and RSVB7. Interestingly, RSVA is more common than RSV B and may lead to more severe illness and even death if it causes an infection8. However, all RSV genotypes display a range of pathogenicity8. Different RSV genotypes can co-epidemic at the same time and place. However, the majority of epidemics are dominated by one of the subgroups or genotypes15. In China, the ON1 RSVA genotype and the BA9 RSVB genotype have recently been the two most prevalent genotypes16. This is because; RSV shares the high mutation rate of other RNA viruses (103 to 104). However, only the G gene was confirmed to have mutated in vivo research, despite in vitro evidence suggesting that both the G and SH genes are more susceptible to spontaneous mutations than any other portion of the RSV genome17. In response to immunological pressure, circulating RSV seems to undergo persistent alterations in sequence and antigenicity, particularly in the G protein10. However, duplication in the C-terminal region of the attachment (G) glycoprotein (ON1-like genotype) of RSVA was first discovered in 2010 in Canada17. Furthermore, an RSV epidemic was described in Australia during the COVID-19 era of 2020–2021, particularly affecting the ON1 genotype of RSVA, with many point mutations detected in the C-terminal region of the attachment (G) glycoprotein, in addition to the nucleocapsid and tiny hydrophobic proteins18. Therefore, mutations to these proteins increase the viral epidemic propensity, drug resistance, and immune tolerance.Interestingly, two membrane proteins of the RSV genome envelop, one of which helps with host cell attachment and the other with fusionTherefore, by considering all of the global issues, we determined to conduct a comprehensive genome study of RSV in which the purpose of this research was to examine the differences in mutations between RSV subtypes A and B, as well as their transmission, phylogenetic, and phylodynamic analyses. We expect this research to be instrumental in developing an effective RSV preventative and addressing severe respiratory conditions such as viral lower respiratory tract infections worldwide.38 and estimated that RSV-A and RSV-B appeared around 1953 and 1956, respectively. In addition, we observed significant variations in the virus circulating in various countries at different times. Overall, RSV-A was present in a broader number of countries than RSV-B  has been demonstrated to be significantly influenced by mutation and recombination in previous studies. RSVA's genetic and phenotypic evolution is primarily driven by selection dynamicsns Table .Table 1SIn our study, we found that the genomes of RSV A and RSV B contain a high number of unique mutations. There were 13,408 unique mutations in RSV A, including 8,540 synonymous mutations and 4,813 missense mutations. RSV B had a total of 10,922 unique mutations, including 6,638 synonymous mutations and 4,182 missense mutations . We performed LD analysis to evaluate the degree of genetic linkage between single nucleotide polymorphisms (SNPs) and haplotypes. Our analysis indicated that there was a low level of genetic linkage between SNPs and haplotypes . Nucleotide diversity in populations may change due to natural selection. Further, Shannon's entropy values for all the genes were relatively high, ranging from 0.307252 for the phosphoprotein to 0.673744 for the attachment glycoprotein, indicating a high degree of heterogeneity within the genes  was the attachment glycoprotein with a value of 0.02861, followed by the polymerase protein and the fusion glycoprotein, while the lowest diversity was found in the gene of M-2 protein with a value of 0.00533. A high degree of diversity exists within the gene sequences as evidenced by Shannon's entropy values, which ranged from 0.272656 for nonstructural protein 1 to 0.953729 for small hydrophobic protein  therapeutics and diagnostics. Understanding RSV's genetic variability is important to develop effective diagnostic tools and treatment strategies. An extensive mutational study can be used to identify a drug target or vaccine epitope targeting structural proteins against the virus. Linkage distribution data could be incorporated along with mutational data in order to gain insights about haplotypes and develop targeted antiviral therapies to increase their effectiveness. Further, in-silico drug design approaches could be used to develop antiviral compounds specifically targeting critical regions of the virus. The data can be incorporated into ongoing surveillance systems to monitor the emergence of new strains and potential outbreaks, assist public health authorities in planning and responding promptly, and develop diagnostic tools. Overall, our research findings will help develop therapeutic and diagnostic drugs, aiding in identifying drug targets, in-silico drug design, rapid diagnostic tests, and tracking viral variants for effective control and treatment.19. All of the sequences were then screened for quality before further processing, and those with gaps were thrown out. According to GISAID, the EPI_ISL_412866 and EPI_ISL_1653999 sequences were chosen as reference sequences for the RSV A and B subtypes, respectively.The Global Initiative for Sharing All Influenza Data (GISAID) has been searched for all submitted Respiratory syncytial virus subtype A and B genomic sequences as of December31, 202220, followed by the construction of a maximum likelihood phylogenetic tree using the IQ-TREE tool with a bootstrap value of 100021. After that, we reconstructed the tree using the TreeTime tool22 so that we could have a clear understanding of the chronological relationship. We then annotated the reconstructed tree with geography information and visualized it using the iTOL server23. Based on the same procedure, we constructed phylogenetic trees for both RSV A and RSV B, which were then used to construct their transmission network using StrainHub24. Lastly, we classified the sequences into different haplotype groups and analyzed their chronological distribution over time at different geographical locations as well as their back-and-forth movement in different parts of the world using the AutoVem2 tool25.Firstly, the selected sequences were aligned using the Mafft algorithm26 was used to align all the sequences of RSV A and RSV B against the relevant references, and Samtools was used to call the variants from the alignments. Further, SNP-sites27 were also used to detect mutations in the sequences, and only common mutations were analyzed downstream. Afterwards, SNPeff28 was used to predict the effects of the mutations. Haploview29 was used to detect linkage disequilibrium among the mutations with the highest prevalence and presented as R2 index, whereas the lollipops tool was used to prepare the lollipop plots of those mutations. In general, R programming was used for data preparation and analysis.The minimap2 algorithm30 to estimate nucleotide diversity and Tajima's D (π) using a 20 base-pair window at five base-pair steps. In addition, Shannon's Entropy was calculated using DiMA31. In the next step, we analyzed the direction of selection in the sequences to determine whether diversity moves away from neutrality and to understand the pattern of evolution using the SLAC algorithm32 in the HyPhy software33. As a final step, FEL32 and FUBAR34 methods were employed to identify specific sites that were experiencing diversifying or purifying selection.First, we used TASSEL softwareSupplementary Information.


Objective Infection and exposure of the implant are some of the most common and concerning complications after implant-based breast reconstruction. Currently, there is no consensus on the management of these complications. The aim of the present study was to review our cases and to present a clinical protocol.Methods We conducted a retrospective review of consecutive patients submitted to implant-based breast reconstruction between 2014 and 2016. All patients were managed according to a specific and structured protocol.Results Implant exposure occurred in 33 out of 277 (11.9%) implant-based reconstructions. Among these, two patients had history of radiotherapy and had their implant removed; Delayed reconstruction with a myocutaneous flap was performed in both cases. Signs of severe local infection were observed in 12 patients, and another 5 presented with extensive tissue necrosis, and they were all submitted to implant removal; of them, 8 underwent reconstruction with a tissue expander, and 2, with a myocutaneous flap. The remaining 14 patients had no signs of severe infection, previous irradiation or extensive tissue necrosis, and were submitted to primary suture as an attempt to salvage the implant. Of these, 8 cases (57.1%) managed to keep the original implant.Conclusion Our clinical protocol is based on three key points: history of radiotherapy, severe infection, and extensive tissue necrosis. It is a practical and potentially-reproducible method of managing one of the most common complications of implant-based breast reconstruction. The rate of postmastectomy breast reconstruction (PMBR) has increased worldwide.Of all possible complications, implant infection and exposure remain major concerns, as they can lead to implant loss and bad cosmetic results.Traditionally, implant infection is treated with antibiotic therapy, removal of the implant, and delayed reconstruction.In face of the lack of structured and clear information concerning the management of patients with implant exposure with or without infection after breast reconstruction, in the present manuscript, we review our cases and provide a clinical roadmap for the management of these patients.We conducted a retrospective review of consecutive patients submitted to implant-based breast reconstruction between January 1st, 2014, and June 30st, 2016. Mastectomies were performed by one of seven surgeons of Breast Unit of Hospital Nossa Senhora das Graças, in the city of Curitiba, Southern Brazil. The same surgeon performed all breast reconstructions and managed the complications. Preoperative antibiotic prophylaxis with 2 g of Cefazolin was administrated in every case. Clindamycin was used for patients allergic to β-lactams. We used implants from two manufacturers: Allergan plc , and Mentor Worldwide LLC . The study was approved by the local Ethics Committee (under protocol no. 178.554).The following demographic data were analyzed for each patient: age, presence of comorbidities, body mass index (BMI), smoking, previous breast surgeries, chemotherapy, radiotherapy, and axillary dissection. Regarding the surgical technique, the following data were evaluated: type of mastectomy (nipple-sparing or skin-sparing mastectomy), use of autologous tissue, timing of reconstruction (immediate or delayed), type of protheses (definitive or temporary), and breast weight. The type of reconstruction was defined individually for each patient by the surgical team, considering oncological staging, the patients' desire, biophysical characteristics, type of surgery, risk factors, and adjuvant treatment. Patients submitted to breast reconstruction with a different team of surgeons, those submitted to cosmetic surgeries, those with follow-up shorter than 3 months, and patients initially submitted to reconstruction with a myocutaneous flap were excluded.The patients were treated according the same management protocol . BrieflSevere implant infection was defined as local inflammatory signs , with or without purulent discharge, associated with systemic inflammatory response . Necrosis of the flap was defined as absence of vitality of the overlying tissue, causing loss of function. Extensive necrosis is defined when there is no possibility of approaching the viable tissues surrounding the lesion.t-test was used for the continuous variables, and the Mann-Whitney U test, for the ordinal variables. Values ofp < 0.05 were considered statistically significant. The software used was the Epi Info , version 7.Descriptive data was presented as frequencies and percentages. The Pearson Chi-squared test was used to compare the rates of complications of each risk factor, and Fisher exact test was used when necessary. The StudentA total of 277 mastectomies with implant-based reconstruction were performed in 232 patients in the period analyzed. Of the 45 contralateral mastectomies performed, 32 (71.1%) were prophylactic , and 13 (28.9%) were oncologic (synchronic tumors). The mean follow-up was of 19.2 months.2(64.3%). Of all patients, 12.3% had history of smoking, and 27.4% received neoadjuvant chemotherapy. In total, 56 patients had 1 or more complications (20.2%); of these, 36 needed hospitalization. The most common complication was implant exposure , followed by small tissue necrosis , severe infection  and extensive necrosis . The mean time between surgery and prosthesis exposure was of 7 weeks.2and 30 kg/m2was found among patients with exposure than among those without it (30.3% (n = 10 out of 33) versus 22.9% (n = 56 out of 244) respectively), as well as a higher proportion of BMIs above 30 kg/m2(21.2% versus 10.7% respectively), but these findings were not statistically significant . Among patients with implant exposure there was also a higher proportion of axillary dissection (27.3% (n = 9 out of 33) versus 18.9% (n = 46 out of 244) among patients without exposure), although this difference was not statistically significant.n = 6), or did not have success with the second attempt (n = 1).In total, 19 patients had no signs of severe infection or previous irradiation; of these, 5 (26.3%) presented with extensive tissue necrosis . All ofn = 268).At the end of the follow-up, reconstruction was successful in 24 (72.7%) out of 33 patients with prosthesis exposure. Considering all 277 patients, our success rate was of 96.7%  had their device salvaged. Therefore, the literature supports the decision contained in our protocol to remove the implant of the patients with severe infection and prosthesis exposure.The second parameter to be analyzed is if the patient with the prosthesis exposed presents signs of severe infection. In that case, the implant is removed, and the patient receives systemic antibiotics. A delayed reconstruction is proposed after at least three months. Most authors who investigated the possibility of salvaging infected implants excluded patients with severe infection.The last parameter is if there is extensive tissue necrosis. In this situation, there is no possibility of approximating the viable tissues surrounding the lesion, and the implant needs to be removed. If there is no sign of severe infection, no history of radiotherapy, and no extensive tissue necrosis, a primary suture is indicated. This approach was successful in 8 out of 14 patients (57.1%) in the present study. Two studiesThere are limitations to the present study. First, the small number of patients with implant exposure was insufficient to demonstrate which risk factors are associated with this complication. However, it is important to emphasize that this was not the aim of the present study, as other authors have already investigated this subject. Second, the protocol presented needs to be validated by other groups of surgeons, as well as the patients' acceptance of its proposals.Our clinical protocol combines the evidence from the literature, clinical and individualized data of the patient, and the experience of a surgeon specialized in breast reconstruction. This protocol, based on three key points , is a practical and potentially-reproducible method of managing one of the most common complications of implant-based breast reconstruction.


Invasive infections with beta-haemolytic streptococci of Lancefield groups A (iGAS), B (iGBS) and C/G (iGCGS) are a major cause of morbidity and mortality worldwide.We studied incidence trends of invasive beta-haemolytic streptococcal infections in Finland, focusing on iGCGS.We conducted a retrospective register-based study. Cases were defined as isolations from blood and/or cerebrospinal fluid and retrieved from the National Infectious Disease Register where all invasive cases are mandatorily notified.Between 2006 and 2020, the mean annual incidence was 4.1 per 100,000 for iGAS (range: 2.1–6.7), 5.2 for iGBS (4.0–6.3) and 10.1 for iGCGS (5.4–17.6). The incidence displayed an increasing trend for all groups, albeit for iGBS only for individuals 45 years and older. The increase was particularly sharp for iGCGS . The incidence rate was higher in males for iGCGS (adjusted incidence rate ratio (IRR) = 1.6; 95% confidence interval (CI): 1.5–1.8) and iGAS ; for iGBS, the association with sex was age-dependent. In adults, iGCGS incidence increased significantly with age. Recurrency was seen for iGCGS and secondarily iGBS, but not for iGAS. Infections with iGCGS and iGBS peaked in July and August.The incidence of invasive beta-haemolytic streptococcal infections in Finland has been rising since 2006, especially for iGCGS and among the elderly population. However, national surveillance still focuses on iGAS and iGBS, and European Union-wide surveillance is lacking. We recommend that surveillance of iGCGS be enhanced, including systematic collection and typing of isolates, to guide infection prevention strategies. What did you want to address in this study?Beta-haemolytic streptococci can cause severe invasive infections with considerable morbidity and mortality. In this study we wanted to investigate whether the incidence of this type of infections has changed over the 15-year period 2006 to 2020 in Finland. We additionally wanted to identify population groups with an increased risk for this type of infections.What have we learnt from this study?In Finland, over the period 2006 to 2020, there was an increase in the incidence of invasive infections caused by beta-haemolytic streptococci. The sharpest increase was observed for infections caused by streptococci belonging to Lancefield groups C/G, which mostly affected older age groups.What are the implications of your findings for public health?The observation of a steep rise in invasive infections caused by streptococci of groups C/G is of concern and warrants further investigation. To this end, we propose that the surveillance of this type of infections be enhanced. Beta-haemolytic streptococci are important bacterial pathogens, known to cause considerable morbidity and mortality worldwide both in adults and in children -4.Streptococcus pyogenes) and group B . Streptococci belonging to groups C (GCS) and G (GGS), predominantly of the species S. dysgalactiae subspecies equisimilis, can also cause human infections, and their importance is increasingly being acknowledged [S. dysgalactiae subspecies equisimilis can exhibit group C, group G and also sometimes group A antigens. Besides Lancefield serotyping, emm typing can be used for molecular typing of GAS, GCS and GGS; it is based on polymorphisms in the emm gene that encodes the M protein, a major streptococcal virulence factor [Beta-haemolytic streptococci are traditionally classified into Lancefield serogroups . The twoowledged -8. The se factor ,10.S. dysgalactiae and S. pyogenes [Infections caused by beta-haemolytic streptococci present with a wide clinical range, from mild superficial infections to severe life-threatening invasive diseases. Invasive GAS infections (iGAS) may be fulminant and cause considerable mortality. Typical clinical manifestations include bacteraemia, necrotising fasciitis and toxic shock syndrome. Although less frequent than non-invasive GAS diseases, their global burden is high, with 163,000 associated deaths per year based on a 2005 estimate [pyogenes . AsymptoInvasive streptococcal infections in Finland are mandatorily notified by the clinical microbiological laboratories to the National Infectious Disease Register (NIDR) of the Finnish Institute for Health and Welfare (THL) since 1995. All iGAS and iGBS isolates are sent to the reference laboratory of THL for surveillance purposes, with the possibility for typing. In contrast, iGCGS isolates are processed at the local laboratory level and not collected in a centralised manner, although iGCGS findings are also notifiable.The aim of this study was to describe the changes in the incidence trends of invasive beta-haemolytic streptococcal infections in Finland over the 15-year period 2006 to 2020, with a focus on iGCGS, for which published studies at a national level are lacking. An invasive beta-haemolytic streptococcal infection was defined as the isolation of beta-haemolytic streptococci from a blood or cerebrospinal fluid (CSF) specimen (NIDR case definition). In Finland, invasive beta-haemolytic streptococcal isolates are notified by local laboratories to the NIDR. Multiple notifications for the same individual are combined into a single case, when received within 3 months from first isolation.S. pyogenes, group B streptococci, S. agalactiae, group C streptococci, group G streptococci, S. dysgalactiae ssp. equisimilis, S. dysgalactiae ssp. dysgalactiae, S. equi ssp. zooepidemicus, S. equi ssp equi, S. canis. Case notification data included the national personal identification number, age, sex, specimen type, microbial species, Lancefield group and date of death. Emm-typing is not done as part of routine surveillance for iGCGS. As this information was lacking for most of these isolates, we decided not to include this variable in the analysis. Cases were dated based on the date of specimen collection or, in the few cases where that was not available, on the date when the notification was filed to the NIDR. Each calendar year spanned 1 January to 31 December.Our study included all NIDR case notifications of isolations from blood or CSF with date of sampling between 1 January 2006 and 31 December 2020, with either of the following entries: group A streptococci, The descriptive analysis included the calculation of interquartile ranges (IQR). Infants were defined as children younger than 1 year. Neonatal early-onset GBS disease was defined as occurring during the first 6 days of life, and late-onset between days 7 and 89. Multiple notifications for the same individual concerning the same Lancefield group were considered as repeat infections. The 7-day and 30-day case fatality ratios (CFR) were defined as the proportion of cases who passed away within, respectively, 7 and 30 days from the date of the case notification, which corresponded to the date of specimen collection in all but two cases.To calculate incidence rates, mean population data for Finland, defined as the average of the populations of two consecutive years  were retrieved from Statistics Finland. Age distributions between Lancefield groups were compared with a Wilcoxon rank sum test. To calculate trends in incidence rates while assessing their possible associations with age, sex and year of isolation, we used negative binomial regression. The need for interactions between explanatory variables in the model was assessed by Akaike information criterion or Bayesian information criterion. In all cases, there were age–sex interactions. For iGAS and iGCGS, we found no evidence of interaction between the annual trend and age or sex, except for a low-level interaction in ages 85 years and above. For iGBS, there were annual trend differences in several age groups, which we addressed by switching to a random (mixed) effect Poisson regression model.Supplementary Tables S1 and S2. Seasonality was evaluated with Poisson regression, with year and month as independent variables, using monthly incidence data. We also ran the model with incidence data adjusted for the number of days per month. We calculated IRR per calendar year and month, adjusted for calendar month and calendar year, respectively.With the aid of the models, we calculated incidence rate ratios (IRR), adjusted for the independent variables used in the respective models as further specified in All statistical analyses were carried out in Stata, version 17.0 (StataCorp LLC). P values below 5% or non-overlapping 95% confidence intervals (CI) were considered statistically significant. In cases of minimally overlapping 95% CIs and large differences in point values, statistical significance was confirmed with additional tests, where applicable.Between 2006 and 2020, THL received a total of 15,781 notifications of invasive beta-haemolytic streptococcal findings: 15,663 (99.2%) from blood specimens, 29 (0.2%) from CSF and 89 (0.6%) from both. Of the notifications, 3,352 (21.2%) concerned iGAS, 4,190 (26.6%) iGBS and 8,239 (52.2%) iGCGS. On average, THL received 223 iGAS (range: 162–372), 279 iGBS (range: 213–350) and 549 iGCGS (range: 287–974) notifications annually. The respective mean annual incidence rate was 4.1 (iGAS), 5.2 (iGBS) and 10.1 (iGCGS) per 100,000 population. The annual incidence rate fluctuated over the years, ranging between 2.1 and 6.7 per 100,000 population for iGAS, between 4.0 and 6.3 per 100,000 population for iGBS and between 5.4 and 17.6 per 100,000 population for iGCGS, peaking in 2018 and 2019 .Among the 512 neonatal cases of iGBS, 283 (55%) were early-onset and 229 (45%) late-onset. The mean annual incidence rate among infants was 63.0 per 100,000, in contrast to 4.6 per 100,000 for the rest of the population.Supplement. For iGBS, there were differences in the trends between age groups, with a significantly increasing trend among those 45 years and older, a stable or slightly decreasing trend among those aged 1–44 years, and a significantly decreasing trend among infants. Further details are appended in Supplementary Table S1.Over the 15-year period from 2006 to 2020, the mean annual incidence rate of invasive beta-haemolytic streptococcal infections showed an increasing trend for iGAS and iGCGS . The incThe age–sex distribution of cases differed between the three Lancefield groups . The medSupplementary Table S2. The association with age was stronger for males than females  presented with a single episode of invasive infection. The maximum number of notifications for the same individual was two. The median interval between first and second episode was 404 days ; however, this result should be interpreted with caution, because the number of iGAS repeat infections was small.Repeat infections were more common for iGBS , with up to four notifications for the same individual. Sixty-four per cent of the individuals with repeat notifications were female. There were no cases of repeat infection among infants; the median age of the individuals at second infection was 68 years (IQR: 59–78) and the median interval between first and second episode was 455 days .Repeat infections were most common for iGCGS, affecting more than 6% of the iGCGS-infected individuals. The multitude of episodes was up to six episodes for the same individual. Of the cases with repeat notifications, 56% were male. The median age upon the second and third notified infection episode was 73 and 74 years, respectively (IQR for second episode: 63–81 years) and the median interval between first and second episode was 481 days .There were no deaths caused by iGAS or iGCGS among infants. In contrast, there were six deaths among infant cases with iGBS . All deaths occurred within 7 days from sampling, corresponding to a 7-day CFR of 1.1% for this age group. The 7-day and 30-day CFR for those aged ≥ 1 year are shown in Supplementary Figures S1–S4. Moreover, we compared the monthly and yearly variation in incidence in a Poisson model and used it to predict monthly and yearly incidence trends .To identify seasonal trends, we plotted monthly iGAS, iGBS and iGCGS cases with moving averages. The individual graphs can be found in e trends . FurtherSupplementary Figure S5, where we additionally provide the monthly incidence rate of iGBS per 100,000 population among individuals older than 1 year.In terms of monthly trends, for iGAS we observed a possible incidence peak in December and January, which was, however, not statistically significant . There wSupplementary Table S3 and Figures S1–S4.In terms of annual variation, 2012 was an atypical year for iGCGS infections, with fewer cases than expected. For iGAS and iGBS, there was a modest dip in incidence in 2011. Detailed results on the annual variation can be found in Our registry-based study shows that the incidence of iGAS, iGBS  and, in particular, iGCGS in Finland increased over the 15-year period of 2006 to 2020, peaked in 2018 and 2019 and then subsided in 2020. In 2020, COVID-19 pandemic restrictions were introduced, which greatly impacted the incidence of all infectious diseases with a person-to-person mode of transmission.The mean annual incidence rate of iGAS was 4.1 (range: 2.1–6.7) per 100,000 population. This is in line with earlier reports, both from Finland -14 and wInfections with iGBS occurred at a mean annual incidence rate of 5.2 per 100,000 (range: 4.0–6.3). This is approximately twice as high as in the years 1995 to 2000, despite a decreasing trend in iGBS among infants, an age group with a high incidence rate [For iGCGS, we observed a sharply increasing trend , with a mean annual incidence of 10.1 per 100,000. As a result of this marked upsurge, iGCGS infections surpassed those of iGAS and iGBS during the study period and constituted in 2020 the majority of invasive beta-haemolytic streptococcal infections in Finland. This upwards trend was noted previously in Finland in a small regional study by Rantala et al., covering the years 1995 to 2004 , but alsemm types and severe iGCGS has been proposed as well [Overall, beta-haemolytic streptococcal infections seem to be increasing in Finland as well as worldwide. The reasons behind this are not clear and are likely to be multiple, encompassing both host and pathogen characteristics. For iGCGS, a partial explanation could be an improvement in diagnostic methods and microbial classification, as well as an increase in the frequency of performing blood cultures . However as well ,30.Invasive beta-haemolytic streptococcal infections exhibited some seasonal patterns. For iGAS, we noted a statistically significant dip in infections in August and autumn, but no clear incidence peaks. Previous studies have observationally noted peaks in winter and early spring ,19,31,32We also noted differences between the Lancefield groups in terms of age and sex of cases, consistent with previous reports ,15,16,32Interestingly, we noted a considerable number of repeat invasive infections with iGCGS and to a lesser extent also with iGBS. In contrast, repeat invasive infections with iGAS were rare. This difference has been noted earlier, but only in smaller studies, with fewer cases of recurrency ,18,35,36Invasive beta-haemolytic infections can be severe and potentially fatal. In our study, iGAS were associated with the highest mortality within the first week after diagnosis. Given the younger structure of the affected population, it is possible that iGAS are more aggressive than iGBS and iGCGS. In contrast, iGCGS appear to be less severe in younger ages; no deaths caused by GCGS were recorded among individuals younger than 30 years. Interestingly, at 30 days after notification, differences in mortality became less pronounced, and the CFR of iGCGS approached that of iGAS, at the level of 9–10%. The 30-day CFR of 9–10% is comparable to that reported for iGAS in earlier studies ,14-17; fDespite the concerning observation of a continuously increasing incidence of beta-haemolytic streptococcal infections, systematic surveillance, especially for iGCGS, is lacking in many countries and at a European level. In many countries, iGCGS infections are not listed as notifiable diseases . In FinlSurveillance is further hampered by the grouping of isolates into Lancefield groups, even though groups overlap and comprise species with disparate features and pathogenicity . The draWhen interpreting our results, a number of limitations should be taken into account. Firstly, the Finnish case definition used here is solely laboratory-based and does not encompass isolations from sites beyond blood/CSF, nor clinical criteria as is the case in some other countries. By excluding clinical criteria, we may have missed deep tissue infections or cases where prompt antibiotic treatment contained the infection, precluding bacterial isolation from the specimen at the time of sampling. Secondly, we grouped iGCS and iGGS together, although they comprise diverse species, with possibly differing pathogenic properties. Finally, our register-based study did not include information on clinical presentations, treatment, underlying conditions or cause of death. On the other hand, our retrospective nationwide register-based study was based on an exceptionally comprehensive and large surveillance dataset, thanks to the mandatory notification of invasive streptococcal infections. Our study has highlighted the need for enhanced attention to invasive beta-haemolytic streptococcal infections, which are becoming more frequent. Invasive iGCGS infections are of particular concern, due to inadequate surveillance and a lack of studies on this topic. Invasive iGAS and iGCGS diseases may be more dissimilar than previously thought, as they differ considerably in various respects, such as age–sex distribution, recurrence and seasonal patterns.


BackgroundCoronavirus (COVID-19) was officially declared a pandemic in March 2020 and has had a major impact on global healthcare services, including radiology. However, little is known about the full impact of COVID-19 on the utilization of diagnostic imaging in Africa’s public healthcare sector.ObjectivesThe objective of this study was to compare public sector diagnostic imaging utilization by modality for the whole Western Cape Province (WCP) of South Africa (SA), as well as its metropolitan and rural areas, in 2019 and 2020 in terms of the absolute number of investigations and investigations per 1000 people.Method people. We calculated mammography utilization for women aged 40-70 years and compared data for 2019 and 2020.We performed a retrospective analysis of Western Cape Government Department of Health and Wellness and Stats SA District Council 2021 Mid-Year Population Estimates data. All diagnostic imaging investigations performed in 2019 and 2020 were collated and stratified by imaging modality, geographic region , and calendar year. Data are presented as the total number of investigations and investigations per 1000Resultsvs. 1,123,508, −261,433) and 20% (262/103vs. 208/103), respectively. Total numerical decline was highest in plain radiographs , accounting for more than three-quarters (78%) of the total reduction.Between 2019 and 2020, the provincial population increased by 1.9%, while total imaging investigations and investigations per 1000 people decreased by 19% , whereas computed tomography was the least impacted  with the remaining modalities decreasing between approximately one-quarter and one-fifth . Proportional metropolitan (−18.7%) and rural decreases (−19.3%) were similar.Percentage decline was most pronounced for mammography, as utilization was almost halved (15.7/10ConclusionCOVID-19 had a substantial impact on WCP imaging services, decreasing overall radiological investigations by almost one-fifth. The greatest impact was on elective investigations, particularly mammography. Although the proportional impact was similar for the metropolitan and rural areas, COVID-19 nonetheless exacerbated existing discrepancies in imaging utilization between the geographical regions. The medium- and long-term clinical impacts of decreased imaging are still to be defined. Severe acute respiratory syndrome coronavirus 2 was first reported in Wuhan, China, on December 31, 2019, and officially declared a pandemic on March 11, 2020. The first case in South Africa (SA) was documented on March 5, 2020, heralding the country’s first coronavirus disease 2019 (COVID-19) “wave,” which extended from March 2020 to November 2020 and peaked during the week of July 5-11 with 13,000 new cases daily. To curtail the spread of infection, a state of national disaster was declared on March 15 . During The pandemic had a major impact on global healthcare, as national authorities, including SA, scaled down routine services and prioritized emergency responses. Outpatient attendance was curtailed, elective surgery was postponed, and staff redeployed from routine services to COVID wards and intensive care units -8. BasicThe pandemic also influenced the nature of emergency care. Individuals showed diminished health-seeking behavior, particularly for less severe illnesses, while trauma admissions declined. In New Zealand, the United Kingdom, France, and Spain, the overall trauma workload decreased by 37%-75% during hard lockdown -13. SA rGiven radiology’s integral role in healthcare  and its Hard lockdown data for April 2020 from Ohio, USA, documented a 55% overall reduction in imaging utilization compared to the previous year. Outpatient, emergency, and inpatient studies decreased by 68%, 48%, and 31%, respectively, while mammography, ultrasound (US), magnetic resonance imaging (MRI), plain radiography, and computed tomography (CT) decreased by 93%, 58%, 56%, 53%, and 47%, respectively. Central and peripheral hospital utilization declined by 42% and 54%-64%, respectively . SimilarStudies of the impact of COVID-19 on imaging utilization have been limited to North America, Europe, and Asia ,17,19. TThis retrospective audit was conducted in the WCP, the southernmost of SA’s nine provinces, with approximately 12% of the national population . The WCPWCP health services are based on mirrored, tiered referral pathways for rural and metropolitan areas . InitialA digital imaging platform is used across the WCP, which has an amalgamated picture-archiving and communication system across various levels of care. Most facilities can view imaging studies performed across the platform, eliminating unnecessary service duplication. The Medical Imaging Services Sub-Directorate (MISSD) within the Directorate of Health Technology (DOHT) in the Western Cape Government Department of Health and Wellness is tasked with the collation of all data pertaining to the utilization of provincial diagnostic imaging services. These data include the utilization of services at each facility and form the basis of this study.We extracted imaging utilization data for 2019 and 2020 from the MISSD database and stratified them by imaging modality  and geographical location . Population statistics for 2019 and 2020 were based on Stats SA District Council 2021 Mid-Year Population Estimates, acquired using a cohort component methodology, and released at mid-year based on the latest available information  by modalWe stratified plain radiographs as either chest X-rays (CXR) or general X-rays. The workload was analyzed by the absolute number of investigations and investigations per 1000 people for each modality, for the whole province, as well as the metropolitan and rural areas. We used breast imaging analyses per 1000 women aged 40-70 years in keeping with a previous WCP analysis of radiological utilization .The study was approved by the Health Research Ethics Committee (HREC) of the Faculty of Medicine and Health Sciences at Stellenbosch University and by the Health Research Committee of the WCP under the auspices of the National Health Research Database .Provincial analysisPopulationIn the review period, the WCP population grew by 1.86% , as seen in Table Overall Imaging UtilizationOverall provincial imaging workload decreased by 19%, or more than a quarter of a million studies . In absolute numbers, the decline was most striking for plain radiographs, which decreased by more than 200,000 investigations  and accounted for more than three-quarters (78%) of the total reduction. The most striking percentage decrease was in mammography, where utilization was almost halved , representing a total decline of 5221 studies. CT was proportionally the least impacted modality, reduced by only 10%, which nonetheless equated to almost 10,000 fewer studies . Other modalities decreased between approximately one-fifth and one-quarter . The proportion of basic radiological investigations (plain radiographs and ultrasound combined) remained relatively constant, being 88.4% and 88.0% in 2019 and 2020, respectively.Imaging Utilization Per 1000 PeopleOverall investigations per 1000 people decreased by one-fifth, or 54 studies (265 vs. 211). Proportional decreases by modality were broadly aligned with those for absolute numbers, as seen in Table Analysis comparing metropolitan and rural areasPopulationAlthough there was an expansion of both the metropolitan  and rural  populations, proportional metropolitan growth exceeded rural growth by 24% (1.99% vs. 1.60%). Overall Imaging UtilizationCombined utilization of plain radiography, US, fluoroscopy, CT, and mammography decreased by 18.7%  and 19.3%  in the metropolitan and rural areas, respectively, with similar proportional reductions in the rural and metropolitan areas . Imaging Utilization Per 1000 People3 people) exceeded rural utilization (228 studies/103 people) by approximately 46 studies/103 people (20%). The most striking discrepancies by modality were for mammography , CT , fluoroscopy , and CXR . General radiography (102.4 vs. 101.9) and US (43.0 vs. 39.5) utilization were similar in the two areas. In 2019, combined metropolitan utilization of plain radiography, US, fluoroscopy, mammography, and CT . However, the patterns of impact were different across the modalities for the two regions. The proportional reduction in metropolitan mammography utilization  exceeded that of rural areas , whereas the proportional rural reduction in fluoroscopy utilization  was higher than that of metropolitan areas .In 2020, both metropolitan and rural regions recorded decreased combined utilization of the above-mentioned modalities  per 1000 people. However, the proportional rural decrease  was slightly greater than the metropolitan decrease , with the resultant increased discrepancy between metropolitan and rural utilization , being approximately four times that of CT (10%) and almost double that of the remaining modalities. The third was the relatively small difference in proportional impact, with the exception of mammography, between the metropolitan and rural areas. This, nonetheless, exacerbated existing discrepancies in imaging utilization between metropolitan and rural areas. The fourth was the broad alignment of findings from this study with those of similar assessments in other healthcare settings.The WCP data show close congruence with those of NHS England , which rThe extent of the impact of COVID-19 on elective WCP investigations is exemplified by the 42% decrease in mammography studies for 2020. The clinical impact of such a contracted mammography service is reflected in the 44% reduction (247 vs. 139) in new breast cancers diagnosed at a large WCP anatomical pathology laboratory in the first three months of lockdown (1 April to 30 June 2020), compared to the corresponding period in 2019 . Substan3 eligible women) compared to the metropolitan baseline (20.5 studies/103 eligible women). It is widely acknowledged that the full clinical significance of curtailed COVID-19 mammographic services is yet to be revealed globally . In the One strength of this study is its foundation on accurate data from all WCP public sector diagnostic imaging facilities, correlated with provincial population data over a two-year period. As such, it provides a robust overview of the impact of the pandemic on a provincial imaging system. The reported data are unique in the SA context and, to our knowledge, across low- and middle-income countries. The work allows appreciation of the elective imaging backlog in certain modalities in the metropolitan and rural areas of the WCP and can assist in future resource allocation, including potential redeployment of staff and resources in the post-COVID era, to address backlogs, particularly in mammography.The study is limited by its retrospective design and the absence of comprehensive demographic data for the imaged population. Additionally, the clinical indications for and acuity of investigations are not provided, while ultrasound, CT, and MRI studies were not stratified by body part. These shortcomings preclude detailed analyses of the clinical impact of decreased imaging during the pandemic. These limitations are common to other published work on the impact of COVID on radiological services and underscore the need for ongoing analyses of the medium- and long-term clinical impacts of the pandemic.COVID-19 had a substantial impact on WCP imaging services, decreasing overall radiological investigations by almost one-fifth. The greatest impact was on elective investigations, particularly mammography. Although the proportional impact was similar for the metropolitan and rural areas, COVID-19 nonetheless exacerbated existing discrepancies in imaging utilization between the geographical regions. The medium- and long-term clinical impacts of decreased imaging are still to be defined.


Hepatitis E virus (HEV) causes acute or chronic hepatitis in humans. Pigs are the primary reservoir for zoonotic HEV genotypes 3 and 4 worldwide. This study investigated the infection dynamics and genomic mutations of HEV in domestic pigs on a farrow-to-finish pig farm in Japan between 2012 and 2021. A high prevalence of anti-HEV IgG antibodies was noted among pigs on this farm in 2012, when the survey started, and persisted for at least nine years. During 2012–2021, HEV RNA was detected in both serum and fecal samples, indicating active viral replication. Environmental samples, including slurry samples in manure pits, feces on the floor, floor and wall swabs in pens, and dust samples, also tested positive for HEV RNA, suggesting potential sources of infection within the farm environment. Indeed, pigs raised in HEV-contaminated houses had a higher rate of HEV infection than those in an HEV-free house. All 104 HEV strains belonged to subgenotype 3b, showing a gradual decrease in nucleotide identities over time. The 2012 (swEJM1201802S) and 2021 (swEJM2100729F) HEV strains shared 97.9% sequence identity over the entire genome. Importantly, the swEJM2100729F strain efficiently propagated in human hepatoma cells, demonstrating its infectivity. These findings contribute to our understanding of the prevalence, transmission dynamics, and genetic characteristics of HEV in domestic pigs, emphasizing the potential risks associated with HEV infections and are crucial for developing effective strategies to mitigate the risk of HEV infection in both animals and humans. Hepatitis E virus (HEV) is a prevalent pathogen responsible for acute or fulminant hepatitis E in humans. It poses a significant public health concern, as it can lead to chronic infection in individuals with compromised immune systems . The HEVHepeviridae, which has rapidly expanded and is now divided into two subfamilies: Orthohepevirinae and the Parahepevirinae, the latter of which consists only of the Piscihepevirus genus, which infects fish  with 1% BSA) against HEV ORF2 (H6210)  tract at the 3′ terminus) and contained three major ORFs, consistent with HEV isolates reported in humans and other animals . The 5′UA comparative analysis revealed a 97.9% sequence identity between the swEJM1201802S and swEJM2100729F strains across the entire genome. Within specific ORFs, the nucleotide sequence identities were 98.0%, 97.5%, and 99.1% for ORF1, ORF2, and ORF3, respectively. In addition, the amino acid sequences exhibited a shared identity of 99.6% in ORF1, 99.7% in ORF2, and 99.1% in ORF3 . A phylo4, 1.0 × 105, and 1.0 × 106 copies/well , obtained from feces of an infected pig in 2021, efficiently propagated in human hepatoma cells, thus demonstrating its infectivity. These findings will help improve our understanding of the prevalence, transmission dynamics, and genetic characteristics of HEV in domestic pigs, underscoring the potential risks associated with HEV infection in both animals and humans. The sequencing of entire HEV genomes obtained from pigs with a time gap of nine years on the identical farm, coupled with the successful cultivation of one of the swine HEV strains derived from a fecal sample, adds significant originality to our present research.The findings in the 2012 study indicated a high prevalence of HEV infection among pigs on the investigated farm, with the presence of anti-HEV IgG antibodies being noted in 100% of 6-month-old pigs and that of HEV RNA in 46.7% of 2-month-old pigs , Table 1In 2012, when the present survey started, HEV RNA was detected exclusively in 2-month-old pigs, while in 2013 and later, it was detectable most frequently in 3-month-old pigs . While tA few longitudinal studies have been conducted to assess the dynamics of infection in pigs ,43,44,45Pigs possess an epithelial-chorial placenta that can prevent IgG from sows being transferred to piglets, but newborn piglets are able to acquire passive immunity through colostrum . PassiveDomestic pigs constitute the main reservoir of zoonotic HEV genotypes 3 and 4. However, more information about its origins and pathways in pig herds is needed to establish measures to prevent further transmissions. As HEV excretion predominantly occurs via feces, it has been reported that manure storage, fecal-contaminated housings and fomites, feed, and drinking water are potential sources of infection . The pre−3 base substitutions per site per year [−3 base substitutions per site per year) [−3 base substitutions per site per year, with the same order as those reported for hepatitis C viruses in a persistently infected chimpanzee (1.44 × 10−3 base substitutions per site per year) [The comparison of partial and entire genomic sequences of HEV strains collected over several years reveals evolutionary changes in the virus. Sequence analyses demonstrated a gradual decrease in nucleotide sequence identities over time, indicating the accumulation of mutations in the HEV strains. The emergence of mutations in previously conserved nucleotide positions, as indicated for partial ORF2 sequences in per year . Comparaer year) ,54. Baseer year) . These fer year) . As a liThe current study also investigated the ability of a swine HEV strain (swEJM2100729F) obtained from feces of a pig in 2021 to propagate in human hepatoma cells. The results demonstrated the efficient propagation of the swine HEV strain, as evidenced by the progressive increase in HEV RNA titer over time, consistent with previous studies ,57. The In order to minimize the risk of human infection, it is crucial to ensure that pigs test negative for HEV at the time they are sent to the slaughterhouse. It is of utmost importance to thoroughly examine the absence of HEV in pigs, particularly in the liver, before they are transported from the farm. According to a study conducted in 2019, rectal fecal samples from all 11 pigs at 6 months tested negative for HEV RNA. This suggests that the pigs designated for slaughter at the investigated farm were devoid of HEV, thus contributing to the reduction in HEV transmission to humans.In conclusion, this study on HEV infection in pigs provides valuable scientific insights into the prevalence, dynamics, and evolutionary changes of the virus. The findings contribute to our understanding of the interplay between HEV and pigs, highlighting the need for robust surveillance, improved biosecurity measures, and public health interventions to minimize the risk of zoonotic transmission. By addressing this important public health issue, our study’s findings have implications for both the livestock industry and human health.