Although testing is widely regarded as critical to fighting the COVID-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics – population testing number and testing coverage – to population mortality outcomes and identify a benchmark for testing adequacy. We aggregated publicly available data through 12 April on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. We found that testing coverage, but not population testing number, was highly correlated with population mortality (rs = −0.79, P = 5.975 × 10−9 vs. rs = −0.3, P = 0.05) and case fatality rate (rs = −0.67, P = 9.067 × 10−6 vs. rs = −0.21, P = 0.20). A testing coverage threshold of 15–45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality; above 45, increased testing did not yield significant incremental mortality benefit. Taken together, testing coverage was better than population testing number in explaining country performance and can serve as an early and sensitive indicator of testing adequacy and disease burden.

In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.

Data on the prevalence of extrapulmonary tuberculosis (EPTB) patients are limited in many African countries including Malawi. We conducted a retrospective review of all histology reports for cancer suspected patients at Mzuzu Central Hospital (MZCH) between 2013 and 2018 to determine the proportion of EPTB cases among cancer suspected patients and characterised them epidemiologically. All reports with inconclusive findings were excluded. In total, 2214 reports were included in the review, 47 of which reported EPTB, representing 2.1% (95% CI 1.6−2.8). The incidence of EPTB was significantly associated with sex, age and HIV status. Men were more than twice (OR 2.1; 95% CI 1.2–3.9) as likely to have EPTB as women while those with HIV were more than six times (OR 6.4; 95% CI 1.7–24.8) as likely to have EPTB compared to those who were HIV-negative. EPTB demonstrated an inverse relationship with age. The highest proportion of EPTB was found from neck lymph nodes (10.3% (5.4–17.2)). A reasonable number of EPTB cases are diagnosed late or missed in Malawi's hospitals. There is a need for concerted efforts to increase EPTB awareness and likely come up with a policy to consider EPTB as a differential diagnosis in cancer suspected patients.

Hypertension represents one of the most common pre-existing conditions and comorbidities in Coronavirus disease 2019 (COVID-19) patients. To explore whether hypertension serves as a risk factor for disease severity, a multi-centre, retrospective study was conducted in COVID-19 patients. A total of 498 consecutively hospitalised patients with lab-confirmed COVID-19 in China were enrolled in this cohort. Using logistic regression, we assessed the association between hypertension and the likelihood of severe illness with adjustment for confounders. We observed that more than 16% of the enrolled patients exhibited pre-existing hypertension on admission. More severe COVID-19 cases occurred in individuals with hypertension than those without hypertension (21% vs. 10%, P = 0.007). Hypertension associated with the increased risk of severe illness, which was not modified by other demographic factors, such as age, sex, hospital geological location and blood pressure levels on admission. More attention and treatment should be offered to patients with underlying hypertension, who usually are older, have more comorbidities and more susceptible to cardiac complications.

Tuberculosis (TB) remains a global public health threat. Misdiagnosis and delayed therapy of sputum smear-negative TB can affect the treatment outcomes and promote pathogen transmission. The application of Xpert MTB/RIF assay in bronchoalveolar lavage fluid (BALF) has been recommended but needs clinical evidence. We carried out a prospective study in the Nanjing Public Health Medical Center from September 2018 to August 2019. Pulmonary tuberculosis (PTB) patients were enrolled in the study if they had negative results of sputum smear. We compared the performance of Xpert MTB/RIF assay in sputum and BALF using sputum culture as the reference. In addition to this, we applied parallel tests using sputum culture, sputum-based Xpert MTB/RIF assay and BALF-based Xpert MTB/RIF assay to jointly detect smear-negative PTB using clinical diagnosis as the reference. With mycobacterial culture as the reference standard, Xpert MTB/RIF of BALF showed a higher sensitivity (14/16, 87.5%), but a relatively lower specificity (57/92, 62.0%). Xpert MTB/RIF of sputum showed relatively lower sensitivity (6/10, 60.0%) and higher specificity (63/88, 71.6%). Compared with sputum culture, Xpert MTB /RIF assay reduced the median detection time of MTB from 30 to 0 days, which significantly shortened the diagnosis time of the smear-negative TB patients. Among the combined detections, the positive detection proportion was improved with significant differences comparing with sputum culture only, from 11.1% (10/90) to 46.7% (42/90) (P < 0.05). Our study showed Xpert MTB/RIF in BALF had a better performance in detecting MTB of smear-negative patients.

Using monthly data from the Ebola-outbreak 2013–2016 in West Africa, we compared two calibrations for data fitting, least-squares (SSE) and weighted least-squares (SWSE) with weights reciprocal to the number of new infections. To compare (in hindsight) forecasts for the final disease size (the actual value was observed at month 28 of the outbreak) we fitted Bertalanffy–Pütter growth models to truncated initial data (first 11, 12, …, 28 months). The growth curves identified the epidemic peak at month 10 and the relative errors of the forecasts (asymptotic limits) were below 10%, if 16 or more month were used; for SWSE the relative errors were smaller than for SSE. However, the calibrations differed insofar as for SWSE there were good fitting models that forecasted reasonable upper and lower bounds, while SSE was biased, as the forecasts of good fitting models systematically underestimated the final disease size. Furthermore, for SSE the normal distribution hypothesis of the fit residuals was refuted, while the similar hypothesis for SWSE was not refuted. We therefore recommend considering SWSE for epidemic forecasts.

With the rapid rise in the prevalence of non-tuberculous mycobacteria (NTM) diseases across the world, the microbiological diagnosis of NTM isolates is becoming increasingly important for the diagnosis and treatment of NTM disease. In this study, the clinical presentation, species distribution and drug susceptibility of patients with NTM disease visiting the Chongqing Public Health Medical Centre during March 2016–April 2019 were retrospectively analysed. Among the 146 patients with NTM disease, eight NTM species (complex) were identified. The predominant NTM species in these patients were identified to be Mycobacterium abscessus complex (53, 36.3%), M. intracellulare (38, 26%) and M. fortuitum (17, 11.7%). In addition, two or more species were isolated from 7.5% of the patients. Pulmonary NTM disease (142, 97.3%) showed the highest prevalence among the patients. It was observed that 40.1% of the patients with pulmonary NTM disease had chronic pulmonary obstructive disease and bronchiectasis, while 22.5% had prior tuberculosis. Male patients showed more association with the conditions of cough and haemoptysis than the female patients. In an in vitro antimicrobial susceptibility testing, most of the species showed susceptibility to linezolid, amikacin and clarithromycin, while M. fortuitum exhibited low susceptibility to tobramycin. In conclusion, the prevalence of NTM disease, especially that of the pulmonary NTM disease, is common in Southwest China. Species identification and drug susceptibility testing are thus extremely important to ensure appropriate treatment regimens for patient care and management.

Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.

Amplifying the testing capacity and making better use of testing resources is a crucial measure when fighting any pandemic. A pooled testing strategy for SARS-CoV-2 has theoretically been shown to increase the testing capacity of a country, especially when applied in low prevalence settings. Experimental studies have shown that the sensitivity of reverse transcription-polymerase chain reaction is not affected when implemented in small groups. Previous models estimated the optimum group size as a function of the historical prevalence; however, this implies a homogeneous distribution of the disease within the population. This study aimed to explore whether separating individuals by age groups when pooling samples results in any further savings on test kits or affects the optimum group size estimation compared to Dorfman's pooling, based on historical prevalence. For this evaluation, age groups of interest were defined as 0–19 years, 20–59 years and over 60 years old. Generalisation of Dorfman's pooling was performed by adding statistical weight to the age groups based on the number of confirmed cases and tests performed in the segment. The findings showed that when the pooling samples are based on age groups, there is a decrease in the number of tests per subject needed to diagnose one subject. Although this decrease is minuscule, it might account for considerable savings when applied on a large scale. In addition, the savings are considerably higher in settings where there is a high standard deviation among the positivity rate of the age segments of the general population.

This study aims to locate the knots of cumulative coronavirus disease 2019 (COVID-19) case number during the first-level response to public health emergency in the provinces of China except Hubei. The provinces were grouped into three regions, namely eastern, central and western provinces, and the trends between adjacent knots were compared among the three regions. COVID-19 case number, migration scale index, Baidu index, demographic, economic and public health resource data were collected from 22 Chinese provinces from 19 January 2020 to 12 March 2020. Spline regression was applied to the data of all included, eastern, central and western provinces. The research period was divided into three stages by two knots. The first stage (from 19 January to around 25 January) was similar among three regions. However, in the second stage, growth of COVID-19 case number was flatter and lasted longer in western provinces (from 25 January to 18 February) than in eastern and central provinces (from 26 February to around 11 February). In the third stage, the growth of COVID-19 case number slowed down in all the three regions. Included covariates were different among the three regions. Overall, spline regression with covariates showed the different change patterns in eastern, central and western provinces, which provided a better insight into regional characteristics of COVID-19 pandemic.

Owing to limited data, we conducted a meta-analysis to re-evaluate the relationship between obesity and coronavirus-2019 (COVID-19). Literature published between 1 January 2020 and 22 August 2020 was comprehensively analysed, and RevMan3.5 was used for data analysis. A total of 50 studies, including data on 18 260 378 patients, were available. Obesity was associated with a higher risk of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) infection (odds ratio (OR): 1.39, 95% confidence interval (CI) 1.25–1.54; P < 0.00001) and increased severity of COVID-19 (hospitalisation rate: OR: 2.45, 95% CI 1.78–3.39; P < 0.00001; severe cases: OR: 3.74, 95% CI 1.18–11.87; P: 0.02; need for intensive care unit admission: OR: 1.30, 95% CI 1.21–1.40; P < 0.00001; need for invasive mechanical ventilation: OR: 1.59, 95% CI 1.35–1.88; P < 0.00001 and mortality: OR: 1.65, 95% CI 1.21–2.25; P: 0.001). However, we found a non-linear association between BMI and the severity of COVID-19. In conclusion, we found that obesity could increase the risk of SARS-CoV2 infection and aggregate the severity of COVID-19. Further studies are needed to explore the possible mechanisms behind this association.

The prevalence of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae urinary tract infections (UTIs) is increasing worldwide. We investigated the prevalence, clinical findings, impact and risk factors of ESBL E. coli/K. pneumoniae UTI through a retrospective review of the medical records of children with UTI aged <15 years admitted to Prince of Songkla University Hospital, Thailand over 10 years (2004–2013). Thirty-seven boys and 46 girls had ESBL-positive isolates in 102 UTI episodes, compared with 85 boys and 103 girls with non-ESBL isolates in 222 UTI episodes. The age of presentation and gender were not significantly different between the two groups. The prevalence of ESBL rose between 2004 and 2008 before plateauing at around 30–40% per year, with a significant difference between first and recurrent UTI episodes of 27.3% and 46.5%, respectively (P = 0.003). Fever prior to UTI diagnosis was found in 78.4% of episodes in the non-ESBL group and 61.8% of episodes in the ESBL group (P = 0.003). Multivariate analysis indicated that children without fever (odds ratio (OR) 2.14, 95% confidence interval (CI) 1.23–3.74) and those with recurrent UTI (OR 2.67, 95% CI 1.37–5.19) were more likely to yield ESBL on culture. Congenital anomalies of the kidney and urinary tract were not linked to the presence of ESBL UTI. In conclusion, ESBL producers represented one-third of E. coli/K. pneumoniae UTI episodes but neither clinical condition nor imaging studies were predictive of ESBL infections. Recurrent UTI was the sole independent risk factor identified.

Only studies in the UK on individuals dying from coronavirus disease 2019 (COVID-19) in hospital have been published, to date. Cremation law requires collection of clinical information that can improve understanding of deaths in both hospital and community settings. Age, sex, date and place of death, occupation, comorbidities and where infection acquired was recorded for all deaths from COVID-19, between 6 April and 30 May, for whom an application was made for cremation at a South Wales' crematorium. Of 752 cremations, 215 (28.6%) were COVID-19 (115 (53.5%) male and 100 (46.5%) female). Median age was 82 years (youngest patient 47 and the oldest 103 years). Over half the deaths (121/215: 56.3%) were over 80 years. Males' odds of dying in hospital, rather than the community were 1.96 times that of females (95% confidence intervals (CI) 1.03–3.74, P = 0.054) despite being of similar age and having a similar number of comorbidities. Only 21 (9.8%) of 215 patients had no comorbidities recorded. Patients dying in care homes were significantly older than those dying in hospital (median 88 years (interquartile (IQ) range 82–93 years) vs. 80 years (IQ range 71–87 years): P < 0.0001). Patients dying in hospital had significantly more comorbidities than those dying in care homes (median 2: IQ range 1–3 vs. 1: IQ range 1–2: P < 0.001). Sixty three (29.3%) of infections were hospital acquired and a further 55 (25.6%) acquired in care homes. In a series, of hospital and community deaths, persons over 80 with an average two comorbidities predominated. Men were more likely to die in hospital. Half the infections were acquired in hospitals or care homes with implications for management of the pandemic.

Pre-existing health conditions may exacerbate the severity of coronavirus disease 2019 (COVID-19). We aimed to estimate the case-fatality rate (CFR) and rate ratios (RR) for patients with hypertension (HBP) and diabetes mellitus (DM) in the New York state. We obtained the age-specific number of COVID-19 confirmed cases and deaths from public reports provided by the New York State Department of Health, and age-specific prevalence of HBP and DM from the Behavioral Risk Factor Surveillance System 2017. We calculated CFR and RR for COVID-19 patients with HBP and DM based on the reported number of deaths with the comorbidity divided by the expected number of COVID-19 cases with the comorbidity. We performed subgroup analysis by age and calculated the CFR and RR for ages of 18–44, 45–64 and 65+ years, respectively. We found that the older population had a higher CFR, but the elevated RRs associated with comorbidities are more pronounced among the younger population. Our findings suggest that besides the elderly, the young population with comorbidity should also be considered as a vulnerable group.

Health care workers (HCWs) are vulnerable to the risk of infections and could become vectors of onward transmission of coronavirus disease 2019 (COVID-19). Little is known about the factors which could contribute to increased COVID-19 infection among HCWs in Nigeria. We aimed at assessing the causes of COVID-19 infection among HCWs. We used a qualitative study design to conduct in-depth interview among 16 frontline HCWs participating in the COVID-19 response in Kwara State, Nigeria. Colaizzi's phenomenological method was used in the qualitative analysis of data. We found that HCWs were aware of their vulnerability to the COVID-19 infection, and the reasons attributed included poor knowledge of IPC measures for COVID-19, inadequate supply of personal protective equipment (PPE), poor political will and inadequate health facilities (HFs) management support. Improved political will and better involvement of HFs management teams in infection prevention and control (IPC) systems are needed to reduce the risk for COVID-19 infection among HCWs. We recommend scale-up training on IPC measures particularly hand washing and use of PPE as well as the development of effective points of care risk assessment with a high index of suspicion in HFs.

Coronavirus disease-2019 (COVID-19) has caused the recent pandemic worldwide. Research studies are focused on various factors affecting the pandemic to find effective vaccine or therapeutics against COVID-19. Environmental factors are the important regulators of COVID-19 pandemic. This study aims to determine the impact of weather on the COVID-19 cases, fatalities and frequency of mutations in Bangladesh. The impacts were determined on 1, 7 and 14 days of the case. The study was conducted based on Spearman's correlation coefficients. The highest correlation was found between population density and cases (rs = 0.712). Among metrological parameters, average temperature had the strongest correlation (rs = −0.675) with the cases. About 82% of Bangladeshi isolates had D614G at spike protein. Both temperature and UV index had strong effects on the frequency of mutations. Among host factors, coinfection is highly associated with frequency of different mutations. This study will give a complete picture of the effects of metrological parameters on COVID-19 cases, fatalities and mutation frequency that will help the authorities to take proper decisions.

A pooled sample analysis strategy for novel coronavirus (severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)) is proposed for a large population in this paper. The population to be tested is divided into divisions based on earlier observed detection rate of SARS-CoV-2 first. Samples collected are then grouped in appropriate pooled size. The number of tests per person in that population is expressed as a function of two variables: the observed detection rate and the pooled size or number of samples grouped. The minimum number of tests per person can be further shown to be a function of only one of these two variables, because these two parameters are found to be related at this minimum. A management scheme on grouping the samples is proposed in order to reduce the number of tests, to save time, which is of utmost importance in fighting an epidemic. The proposed testing scheme will be useful for supporting the government in making decisions to handle regular routine detection tests for identifying asymptomatic patients and implementing health code system in large population of millions of citizens. Another important point is to use smaller number of test kits, allowing more resources to speed up the mass screening tests, particularly in places not so rich.

It is important to understand the temporal trend of the paediatric severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load to estimate the transmission potential of children in schools and communities. We determined the differences in SARS-CoV-2 viral load dynamics between nasopharyngeal samples of infected asymptomatic and symptomatic children. Serial cycle threshold values of SARS-CoV-2 from the nasopharynx of a cohort of infected children were collected for analysis. Among 17 infected children, 10 (58.8%) were symptomatic. Symptomatic children, when compared to asymptomatic children, had higher viral loads (mean cycle threshold on day 7 of illness 28.6 vs. 36.7, P = 0.02). Peak SARS-CoV-2 viral loads occurred around day 2 of illness in infected children. Although we were unable to directly demonstrate infectivity, the detection of significant amount of virus in the upper airway of asymptomatic children suggest that they have the potential to shed and transmit SARS-CoV-2. Our study highlights the importance of contact tracing and screening for SARS-CoV-2 in children with epidemiological risk factors regardless of their symptom status, in order to improve containment of the virus in the community, including educational settings.

The coronavirus disease 2019 (COVID-19) pandemic is currently the most critical challenge in public health. An understanding of the factors that affect severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection will help fight the COVID-19 pandemic. This study sought to investigate the association between SARS-CoV-2 infection and blood type distribution. The big data provided by the World Health Organization (WHO) and Johns Hopkins University were used to assess the dynamics of the COVID-19 epidemic. The infection data in the early phase of the pandemic from six countries in each of six geographic zones divided according to the WHO were used, representing approximately 5.4 billion people around the globe. We calculated the infection growth factor, doubling times of infection and death cases, reproductive number and infection and death cases in relation to the blood type distribution. The growth factor of infection and death cases significantly and positively correlated with the proportion of the population with blood type A and negatively correlated with the proportion of the population with blood type B. Compared with the lower blood type A population (<30%), the higher blood type A population (⩾30%) showed more infection and death cases, higher growth factors and shorter case doubling times for infections and deaths and thus higher epidemic dynamics. Thus, an association exists between SARS-CoV-2 and the ABO blood group distribution, which might be useful for fighting the COVID-19 pandemic.

Arctic rabies virus variant (ARVV) is enzootic in Quebec (Canada) north of the 55th parallel. With climate change, increased risk of re-incursion of ARVV in more densely populated southern regions raises public and animal health concerns. The objective of this study was to prioritise geographical areas to target for an early detection of ARVV incursion south of the 55th parallel based on the historical spatio-temporal trends of reported rabies in foxes in Quebec. Descriptive analyses of fox rabies cases from 1953 to 2017 were conducted. Three periods show increases in the number of fox rabies cases in southern regions and indicate incursion from northern areas or neighbouring provinces. The available data, particularly in central and northern regions of the province, were scarce and of low spatial resolution, making it impossible to identify the path of spread with precision. Hence, we investigated the use of multiple criteria, such as historical rabies cases, human population density and red fox (Vulpes vulpes) relative abundance, to prioritise areas for enhanced surveillance. This study underscores the need to define and maintain new criteria for selecting samples to be analysed in order to detect rapidly ARVV cases outside the current enzootic area and any potential re-incursion of the virus into central and southern regions of the province.