Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04–0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94–2.50) per 100 000 persons per year. The highest excess morbidity and mortality was found in older adults and young children, and during influenza A(H3N2) epidemics.

Backyard chickens are increasingly popular, and their husbandry varies widely. How backyard chickens are housed may influence the accessibility of chicken feed and water to wild birds, and thus, the contact rates between both groups. Increased contacts have implications for pathogen transmission; for instance, Newcastle disease virus or avian influenza virus may be transmitted to and from backyard chickens from contaminated water or feed. Given this potentially increased pathogen risk to wild birds and backyard chickens, we examined which wild bird species are likely to encounter backyard chickens and their resources. We performed a supplemental feeding experiment followed by observations at three sites associated with backyard chickens in North Georgia, USA. At each site, we identified the species of wild birds that: (a) shared habitat with the chickens, (b) had a higher frequency of detection relative to other species and (c) encountered the coops. We identified 14 wild bird species that entered the coops to consume supplemental feed and were considered high-risk for pathogen transmission. Our results provide evidence that contact between wild birds and backyard chickens is frequent and more common than previously believed, which has crucial epidemiological implications for wildlife managers and backyard chicken owners.

West Nile neuroinvasive disease (WNND) is a severe neurological illness that can result from West Nile virus (WNV) infection, with long-term disability and death being common outcomes. Although WNV arrived in North America over two decades ago, risk factors for WNND are still being explored. The objective of this study was to identify WNND comorbid risk factors in the Ontario population using a retrospective, population-based cohort design. Incident WNV infections from laboratory records between 1 January 2002 – 31 December 2012 were individually-linked to health administrative databases to ascertain WNND outcomes and comorbid risk factors. WNND incidence was compared among individuals with and without comorbidities using risk ratios (RR) calculated with log binomial regression.

Three hundred and forty-five individuals developed WNND (18.3%) out of 1884 WNV infections. West Nile encephalitis was driving most associations with comorbidities. Immunocompromised (aRR 2.61 [95% CI 1.23–4.53]) and male sex (aRR 1.32 [95% CI 1.00–1.76]) were risk factors for encephalitis, in addition to age, for which each 1-year increase was associated with a 2% (aRR 1.02 [95% CI 1.02–1.03]) relative increase in risk. Our results suggest that individuals living with comorbidities are at higher risk for WNND, in particular encephalitis, following WNV infection.

Lockdowns have been a core infection control measure in many countries during the coronavirus disease 2019 (COVID-19) pandemic. In England's first lockdown, children of single parent households (SPHs) were permitted to move between parental homes. By the second lockdown, SPH support bubbles between households were also permitted, enabling larger within-household networks. We investigated the combined impact of these approaches on household transmission dynamics, to inform policymaking for control and support mechanisms in a respiratory pandemic context. This network modelling study applied percolation theory to a base model of SPHs constructed using population survey estimates of SPH family size. To explore putative impact, varying estimates were applied regarding extent of bubbling and proportion of different-parentage within SPHs (DSPHs) (in which children do not share both the same parents). Results indicate that the formation of giant components (in which COVID-19 household transmission accelerates) are more contingent on DSPHs than on formation of bubbles between SPHs, and that bubbling with another SPH will accelerate giant component formation where one or both are DSPHs. Public health guidance should include supportive measures that mitigate the increased transmission risk afforded by support bubbling among DSPHs. Future network, mathematical and epidemiological studies should examine both independent and combined impact of policies.

Repeated serosurveys are an important tool for understanding trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination. During 1 September 2020–20 March 2021, the NYC Health Department conducted a population-based SARS-CoV-2 antibody prevalence survey of 2096 NYC adults who either provided a blood specimen or self-reported the results of a previous antibody test. The serosurvey, the second in a series of surveys conducted by the NYC Health Department, aimed to estimate SARS-CoV-2 antibody prevalence across the city and for different groups at higher risk for adverse health outcomes. Weighted citywide prevalence was 23.5% overall (95% confidence interval (CI) 20.1–27.4) and increased from 19.2% (95% CI 14.7–24.6) before coronavirus disease 2019 vaccines were available to 31.3% (95% CI 24.5–39.0) during the early phases of vaccine roll-out. We found no differences in antibody prevalence by age, race/ethnicity, borough, education, marital status, sex, health insurance coverage, self-reported general health or neighbourhood poverty. These results show an overall increase in population-level seropositivity in NYC following the introduction of SARS-CoV-2 vaccines and highlight the importance of repeated serosurveys in understanding the pandemic's progression.

This study is performed to figure out how the presence of diabetes affects the infection, progression and prognosis of 2019 novel coronavirus disease (COVID-19), and the effective therapy that can treat the diabetes-complicated patients with COVID-19. A multicentre study was performed in four hospitals. COVID-19 patients with diabetes mellitus (DM) or hyperglycaemia were compared with those without these conditions and matched by propensity score matching for their clinical progress and outcome. Totally, 2444 confirmed COVID-19 patients were recruited, from whom 336 had DM. Compared to 1344 non-DM patients with age and sex matched, DM-COVID-19 patients had significantly higher rates of intensive care unit entrance (12.43% vs. 6.58%, P = 0.014), kidney failure (9.20% vs. 4.05%, P = 0.027) and mortality (25.00% vs. 18.15%, P < 0.001). Age and sex-stratified comparison revealed increased susceptibility to COVID-19 only from females with DM. For either non-DM or DM group, hyperglycaemia was associated with adverse outcomes, featured by higher rates of severe pneumonia and mortality, in comparison with non-hyperglycaemia. This was accompanied by significantly altered laboratory indicators including lymphocyte and neutrophil percentage, C-reactive protein and urea nitrogen level, all with correlation coefficients >0.35. Both diabetes and hyperglycaemia were independently associated with adverse prognosis of COVID-19, with hazard ratios of 10.41 and 3.58, respectively.

The impact of influenza and pneumonia on individuals in clinical risk groups in England has not previously been well characterized. Using nationally representative linked databases (Clinical Practice Research Database (CPRD), Hospital Episode Statistics (HES) and Office for National Statistics (ONS)), we conducted a retrospective cohort study among adults (≥ 18 years) during the 2010/2011–2019/2020 influenza seasons to estimate the incidence of influenza- and pneumonia-diagnosed medical events (general practitioner (GP) diagnoses, hospitalisations and deaths), stratified by age and risk conditions. The study population included a seasonal average of 7.2 million individuals; approximately 32% had ≥1 risk condition, 42% of whom received seasonal influenza vaccines. Medical event incidence rates increased with age, with ~1% of adults aged ≥75 years hospitalized for influenza/pneumonia annually. Among individuals with vs. without risk conditions, GP diagnoses occurred 2–5-fold more frequently and hospitalisations were 7–10-fold more common. Among those with obesity, respiratory, kidney or cardiovascular disorders, hospitalisation were 5–40-fold more common than in individuals with no risk conditions. Though these findings likely underestimate the full burden of influenza, they emphasize the concentration of disease burden in specific age and risk groups and support existing recommendations for influenza vaccination.

The duration of immunity after first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the extent to which prior immunity prevents reinfection is uncertain and remains an important question within the context of new variants. This is a retrospective population-based matched observational study where we identified the first polymerase chain reaction (PCR) positive of primary SARS-CoV-2 infection case tests between 1 March 2020 and 30 September 2020. Each case was matched by age, sex, upper tier local authority of residence and testing route to one individual testing negative in the same week (controls) by PCR. After a 90-day pre-follow-up period for cases and controls, any subsequent positive tests up to 31 December 2020 and deaths within 28 days of testing positive were identified, this encompassed an essentially vaccine-free period. We used a conditional logistic regression to analyse the results. There were 517 870 individuals in the matched cohort with 2815 reinfection cases and 12 098 first infections. The protective effect of a prior SARS-CoV-2 PCR-positive episode was 78% (odds ratio (OR) 0.22, 0.21–0.23). Protection rose to 82% (OR 0.18, 0.17–0.19) after a sensitivity analysis excluded 933 individuals with a first test between March and May and a subsequent positive test between June and September 2020. Amongst individuals testing positive by PCR during follow-up, reinfection cases had 77% lower odds of symptoms at the second episode (adjusted OR 0.23, 0.20–0.26) and 45% lower odds of dying in the 28 days after reinfection (adjusted OR 0.55, 0.42–0.71). Prior SARS-CoV-2 infection offered protection against reinfection in this population. There was some evidence that reinfections increased with the alpha variant compared to the wild-type SARS-CoV-2 variant highlighting the importance of continued monitoring as new variants emerge.

This study aimed to determine the epidemiology and association of antimicrobial resistance (AMR) among Escherichia coli and Salmonella in Thailand. The E. coli (n = 1047) and Salmonella (n = 816) isolates from pigs, pork and humans were screened for 18 replicons including HI1, HI2, I1-γ, X, L/M, N, FIA, FIB, W, Y, P, FIC, A/C, T, FIIAs, F, K and B/O using polymerase chain reaction-based replicon typing. The E. coli (n = 26) and Salmonella (n = 3) isolates carrying IncF family replicons, ESBL and/or mcr genes were determined for FAB formula. IncF represented the major type of plasmids. Sixteen and eleven Inc groups were identified in E. coli (85.3%) and Salmonella (25.7%), respectively. The predominant replicon patterns between E. coli and Salmonella were IncK-F (23.7%) and IncF (46.2%). Significant correlations (P < 0.05) were observed between plasmid-replicon type and resistance phenotype. Plasmid replicon types were significantly different among sources of isolates and sampling periods. The most common FAB types between E. coli and Salmonella were F2:A-:B- (30.8%) and S1:A-:B- (66.7%), respectively. In conclusion, various plasmids present in E. coli and Salmonella. Responsible and prudent use of antimicrobials is suggested to reduce the selective pressures that favour the spread of AMR determinants. Further studies to understand the evolution of R plasmids and their contribution to the dissemination of AMR genes are warranted.

This study investigated an outbreak in a kindergarten in Wuyi County of acute gastroenteritis concerning a large number of students and teachers. We performed a case-control study, and collected information on the layout of the school, symptoms, onset time of all cases and vomiting sites. A total of 62 individuals fit the definition of probable cases; among these, there were 19 cases of laboratory-confirmed norovirus infection. Nausea and vomiting were the most common symptoms in the outbreak. Seven student norovirus patients vomited in the school. The odds ratio (OR) of norovirus illness was 15.75 times higher among teachers who handled or interacted with student vomitus without respiratory protection than compared to those without this type of exposure (OR 15.75, 95% CI 1.75–141.40). Nine samples were successfully genotyped; eight samples were norovirus GII.2[P16], one sample was norovirus GII.4 Sydney[P16]. This study revealed that improper handling of vomitus is a risk factor of norovirus infection. Therefore, more attention should be given to train school staff in knowledge of disinfection.

India has the third-largest burden of human immunodeficiency virus (HIV) infection in the world. The coronavirus disease 2019 (COVID-19) pandemic has only exposed the cracks in the Indian healthcare infrastructure concerning HIV. The prevalence of HIV in India is more among the destitute or sections of society shrouded by years of social stigma such as prostitutes, truck drivers, transsexuals and intravenous drug users. National AIDS Control Organisation and The Joint United Nations Programme on HIV/AIDS (UNAIDS) organisation have many several efforts over the years to set up counselling and testing centres all over the country and spread awareness about HIV among the masses. COVID-19 pandemic has reversed years of progress made by the same. HIV patients are biologically more susceptible to COVID-19, and the lockdown has led to the loss of jobs, economic crises, shortage of drugs and necessities such as food and housing among this vulnerable population, which can result in lowered CD4-T cell counts in the coming months and make way for dangerous opportunistic infection outbreaks in this population increasing the overall HIV burden of India. This article explores how COVID-19 has impacted India's already existing HIV epidemic and tries to put forth recommendations based on the evidence found to be better prepared in treating the HIV-positive population in India in the face of another catastrophe like the COVID-19.

In November 2019, an outbreak of Shiga toxin-producing Escherichia coli O157:H7 was detected in South Yorkshire, England. Initial investigations established consumption of milk from a local dairy as a common exposure. A sample of pasteurised milk tested the next day failed the phosphatase test, indicating contamination of the pasteurised milk by unpasteurised (raw) milk. The dairy owner agreed to immediately cease production and initiate a recall. Inspection of the pasteuriser revealed a damaged seal on the flow divert valve. Ultimately, there were 21 confirmed cases linked to the outbreak, of which 11 (52%) were female, and 12/21 (57%) were either <15 or >65 years of age. Twelve (57%) patients were treated in hospital, and three cases developed haemolytic uraemic syndrome. Although the outbreak strain was not detected in the milk samples, it was detected in faecal samples from the cattle on the farm. Outbreaks of gastrointestinal disease caused by milk pasteurisation failures are rare in the UK. However, such outbreaks are a major public health concern as, unlike unpasteurised milk, pasteurised milk is marketed as ‘safe to drink’ and sold to a larger, and more dispersed, population. The rapid, co-ordinated multi-agency investigation initiated in response to this outbreak undoubtedly prevented further cases.

Between 21 November and 22 December 2020, a SARS-CoV-2 community testing pilot took place in the South Wales Valleys. We conducted a case-control study in adults taking part in the pilot using an anonymous online questionnaire. Social, demographic and behavioural factors were compared in people with a positive lateral flow test (cases) and a sample of negatives (controls). A total of 199 cases and 2621 controls completed a questionnaire (response rates: 27.1 and 37.6% respectively). Following adjustment, cases were more likely to work in the hospitality sector (aOR 3.39, 95% CI 1.43–8.03), social care (aOR 2.63, 1.22–5.67) or healthcare (aOR 2.31, 1.29–4.13), live with someone self-isolating due to contact with a case (aOR 3.07, 2.03–4.62), visit a pub (aOR 2.87, 1.11–7.37) and smoke or vape (aOR 1.54, 1.02–2.32). In this community, and at this point in the epidemic, reducing transmission from a household contact who is self-isolating would have the biggest public health impact (population-attributable fraction: 0.2). As restrictions on social mixing are relaxed, hospitality venues will become of greater public health importance, and those working in this sector should be adequately protected. Smoking or vaping may be an important modifiable risk factor.

Surveillance data shows a geographical overlap between the early coronavirus disease 2019 (COVID-19) pandemic and the past Q fever epidemic (2007–2010) in the Netherlands. We investigated the relationship between past Q fever and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 2020/2021, using a retrospective matched cohort study.

In January 2021, former Q fever patients received a questionnaire on demographics, SARS-CoV-2 test results and related hospital/intensive care unit (ICU) admissions. SARS-CoV-2 incidence with 95% confidence intervals (CI) in former Q fever patients and standardised incidence ratios (SIR) to compare to the age-standardised SARS-CoV-2 incidence in the general regional population were calculated.

Among 890 former Q fever patients (response rate: 68%), 66 had a PCR-confirmed SARS-CoV-2 infection. Of these, nine (14%) were hospitalised and two (3%) were admitted to ICU. From February to June 2020 the SARS-CoV-2 incidence was 1573/100 000 (95% CI 749–2397) in former Q fever patients and 695/100 000 in the general population (SIR 2.26; 95% CI 1.24–3.80). The incidence was not significantly higher from September 2020 to February 2021.

We found no sufficient evidence for a difference in SARS-CoV-2 incidence or an increased severity in former Q fever patients vs. the general population during the period with widespread SARS-CoV-2 testing availability (September 2020–February 2021). This indicates that former Q fever patients do not have a higher risk of SARS-CoV-2 infection.

In the past 10–15 years, the government of China has made various efforts in tackling excessive antibiotics use. Yet, little is known about their effects at rural primary care settings. This study aimed to determine the impact of government policies and the COVID-19 pandemic on antibiotic prescribing practices at such settings utilizing data from separate studies carried out pre- and during the pandemic, in 2016 and 2021 in Anhui province, China, using identical sampling and survey approaches. Data on antibiotics prescribed, diagnosis, socio-demographic, etc., were obtained through non-participative observation and a structured exit survey. Data analysis comprised mainly descriptive comparisons of 1153 and 762 patients with respiratory infections recruited in 2016 and 2021, respectively. The overall antibiotics prescription rate decreased from 89.6% in 2016 to 69.1% in 2021, and the proportion of prescriptions for two or more classes of antibiotics was estimated as 35.9% in 2016 and 11.0% in 2021. There was a statistically significant decrease in the number of days from symptom onset to clinic visits between the year groups. In conclusion, measures to constrain excessive prescription of antibiotics have led to some improvements at the rural primary care level, and the COVID-19 pandemic has had varying effects on antibiotic use.

Globally, countries have used diverse methods to report data during the COVID-19 pandemic. Using international guidelines and principles of emergency management, we compare national data reporting systems in African countries in order to determine lessons for future pandemics. We analyse COVID-19 reporting practices across 54 African countries through 2020. Reporting systems were diverse and included summaries, press releases, situation reports and online dashboards. These systems were communicated via social media accounts and websites belonging to ministries of health and public health. Data variables from the reports included event detection (cases/deaths/recoveries), risk assessment (demographics/co-morbidities) and response (total tests/hospitalisations). Of countries with reporting systems, 36/53 (67.9%) had recurrent situation reports and/or online dashboards which provided more extensive data. All of these systems reported cases, deaths and recoveries. However, few systems contained risk assessment and response data, with only 5/36 (13.9%) reporting patient co-morbidities and 9/36 (25%) including total hospitalisations. Further evaluation of reporting practices in Cameroon, Egypt, Kenya, Senegal and South Africa as examples from different sub-regions revealed differences in reporting healthcare capacity and preparedness data. Improving the standardisation and accessibility of national data reporting systems could augment research and decision-making, as well as increase public awareness and transparency for national governments.

We propose that postal Change-of-Address (CoA) data can be used to monitor/predict likely second wave caseloads in viral infections around urban epicentres. To illustrate the idea, we focus on the tri-state area consisting of New York City (NYC) and surrounding counties in New York, New Jersey and Connecticut States. NYC was an early epicentre of the coronavirus disease 2019 (Covid-19) pandemic, with a first peak in daily cases in early April 2020, followed by the second peak in May/June 2020. Using CoA data from the US Postal Service (USPS), we show that, despite a quarantine mandate, there was a large net movement of households from NYC to surrounding counties in the period April–June 2020. This net outward migration of households was strongly correlated with both the timing and the number of cases in the second peaks in Covid-19 cases in the surrounding counties. The timing of the second peak was also correlated with the distance of the county from NYC, suggesting that this was a directed flow and not random diffusion. Our analysis shows that CoA data is a useful method in tracking the spread of an infectious pandemic agent from urban epicentres.