As the COVID-19 pandemic continues to escalate and place pressure on hospital system resources, a proper screening and risk stratification score is essential. We aimed to develop a risk score to identify patients with increased risk of COVID-19, allowing proper identification and allocation of limited resources. A retrospective study was conducted of 338 patients who were admitted to the hospital from the emergency room to regular floors and tested for COVID-19 at an acute care hospital in the Metropolitan Washington D.C. area. The dataset was split into development and validation sets with a ratio of 6:4. Demographics, presenting symptoms, sick contact, triage vital signs, initial laboratory and chest X-ray results were analysed to develop a prediction model for COVID-19 diagnosis. Multivariable logistic regression was performed in a stepwise fashion to develop a prediction model, and a scoring system was created based on the coefficients of the final model. Among 338 patients admitted to the hospital from the emergency room, 136 (40.2%) patients tested positive for COVID-19 and 202 (59.8%) patients tested negative. Sick contact with suspected or confirmed COVID-19 case (3 points), nursing facility residence (3 points), constitutional symptom (1 point), respiratory symptom (1 point), gastrointestinal symptom (1 point), obesity (1 point), hypoxia at triage (1 point) and leucocytosis (−1 point) were included in the prediction score. A risk score for COVID-19 diagnosis achieved area under the receiver operating characteristic curve of 0.87 (95% confidence interval (CI) 0.82–0.92) in the development dataset and 0.85 (95% CI 0.78–0.92) in the validation dataset. A risk prediction score for COVID-19 can be used as a supplemental tool to assist clinical decision to triage, test and quarantine patients admitted to the hospital from the emergency room.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.

This study used hospital records from two time periods to understand the implication of COVID-19 on hospital-based deaths in Burundi. The place of COVID-19 symptoms was sought among deaths that occurred from January to May 2020 (during the pandemic) vs. January to May 2019 (before the pandemic). First, death proportions were tested to seize differences between mortality rates for each month in 2020 vs. 2019. In the second time, we compared mean time-to-death between the two periods using the Kaplan–Meier survival curve. Finally, a logistic regression was fitted to assess the likelihood of dying from COVID-19 symptoms between the two periods. We found statistical evidence of a higher death rate in May 2020 as compared to May 2019. Moreover, death occurred faster in 2020 (mean = 6.7 days, s.d. = 8.9) than in 2019 (mean = 7.8 days, s.d. = 10.9). Unlike in 2019, being a male was significantly associated with a much lower likelihood of dying with one or more COVID-19 symptom(s) in 2020 (odds ratio 0.35, 95% confidence interval 0.14–0.87). This study yielded some evidence for a possible COVID-19-related hospital-based mortality trend for May 2020. However, considering the time-constraint of the study, further similar studies over a longer period of time need to be conducted to trace a clearer picture on COVID-19 implication on hospital-based deaths in Burundi.

One of the largest nationwide bursts of the first COVID-19 outbreak occurred in Spain, where infection expanded in densely populated areas through March 2020. We analyse the cumulative growth curves of reported cases and deaths in all Spain and two highly populated regions, Madrid and Catalonia, identifying changes and sudden shifts in their exponential growth rate through segmented Poisson regressions. We associate these breakpoints with a timeline of key events and containment measures, and data on policy stringency and citizen mobility. Results were largely consistent for infections and deaths in all territories, showing four major shifts involving 19–71% reductions in growth rates originating from infections before 3 March and on 5–8, 10–12 and 14–18 March, but no identifiable effect of the strengthened lockdown of 29–30 March. Changes in stringency and mobility were only associated to the latter two shifts, evidencing an early deceleration in COVID-19 spread associated to personal hygiene and social distancing recommendations, followed by a stronger decrease when lockdown was enforced, leading to the contention of the outbreak by mid-April. This highlights the importance of combining public health communication strategies and hard confinement measures to contain epidemics.

Google's ‘Community Mobility Reports’ (CMR) detail changes in activity and mobility occurring in response to COVID-19. They thus offer the unique opportunity to examine the relationship between mobility and disease incidence. The objective was to examine whether an association between COVID-19-confirmed case numbers and levels of mobility was apparent, and if so then to examine whether such data enhance disease modelling and prediction. CMR data for countries worldwide were cross-correlated with corresponding COVID-19-confirmed case numbers. Models were fitted to explain case numbers of each country's epidemic. Models using numerical date, contemporaneous and distributed lag CMR data were contrasted using Bayesian Information Criteria. Noticeable were negative correlations between CMR data and case incidence for prominent industrialised countries of Western Europe and the North Americas. Continent-wide examination found a negative correlation for all continents with the exception of South America. When modelling, CMR-expanded models proved superior to the model without CMR. The predictions made with the distributed lag model significantly outperformed all other models. The observed relationship between CMR data and case incidence, and its ability to enhance model quality and prediction suggests data related to community mobility could prove of use in future COVID-19 modelling.

Understanding risk factors for death from Covid-19 is key to providing good quality clinical care. We assessed the presenting characteristics of the ‘first wave’ of patients with Covid-19 at Royal Oldham Hospital, UK and undertook logistic regression modelling to investigate factors associated with death. Of 470 patients admitted, 169 (36%) died. The median age was 71 years (interquartile range 57–82), and 255 (54.3%) were men. The most common comorbidities were hypertension (n = 218, 46.4%), diabetes (n = 143, 30.4%) and chronic neurological disease (n = 123, 26.1%). The most frequent complications were acute kidney injury (AKI) (n = 157, 33.4%) and myocardial injury (n = 21, 4.5%). Forty-three (9.1%) patients required intubation and ventilation, and 39 (8.3%) received non-invasive ventilation. Independent risk factors for death were increasing age (odds ratio (OR) per 10 year increase above 40 years 1.87, 95% confidence interval (CI) 1.57–2.27), hypertension (OR 1.72, 95% CI 1.10–2.70), cancer (OR 2.20, 95% CI 1.27–3.81), platelets <150 × 103/μl (OR 1.93, 95% CI 1.13–3.30), C-reactive protein ≥100 μg/ml (OR 1.68, 95% CI 1.05–2.68), >50% chest radiograph infiltrates (OR 2.09, 95% CI 1.16–3.77) and AKI (OR 2.60, 95% CI 1.64–4.13). There was no independent association between death and gender, ethnicity, deprivation level, fever, SpO2/FiO2, lymphopoenia or other comorbidities. These findings will inform clinical and shared decision making, including use of respiratory support and therapeutic agents.

Most of the existing prediction models for COVID-19 lack validation, are inadequately reported or are at high risk of bias, a reason which has led to discourage their use. Few existing models have the potential to be extensively used by healthcare providers in low-resource settings since many require laboratory and imaging predictors. Therefore, we sought to develop and validate a multivariable prediction model of death in Mexican patients with COVID-19, by using demographic and patient history predictors. We conducted a national retrospective cohort study in two different sets of patients from the Mexican COVID-19 Epidemiologic Surveillance Study. Patients with a positive reverse transcription-polymerase chain reaction for SARS-CoV-2 and complete unduplicated data were eligible. In total, 83 779 patients were included to develop the scoring system through a multivariable Cox regression model; 100 000, to validate the model. Eight predictors (age, sex, diabetes, chronic obstructive pulmonary disease, immunosuppression, hypertension, obesity and chronic kidney disease) were included in the scoring system called PH-Covid19 (range of values: −2 to 25 points). The predictive model has a discrimination of death of 0.8 (95% confidence interval (CI) 0.796–0.804). The PH-Covid19 scoring system was developed and validated in Mexican patients to aid clinicians to stratify patients with COVID-19 at risk of fatal outcomes, allowing for better and efficient use of resources.

This study aimed to analyse the spatial–temporal distribution of COVID-19 mortality in Sergipe, Northeast, Brazil. It was an ecological study utilising spatiotemporal analysis techniques that included all deaths confirmed by COVID-19 in Sergipe, from 2 April to 14 June 2020. Mortality rates were calculated per 100 000 inhabitants and the temporal trends were analysed using a segmented log-linear model. For spatial analysis, the Kernel estimator was used and the crude mortality rates were smoothed by the empirical Bayesian method. The space–time prospective scan statistics applied the Poisson's probability distribution model. There were 391 COVID-19 registered deaths, with the majority among ⩾60 years old (62%) and males (53%). The most prevalent comorbidities were hypertension (40%), diabetes (31%) and cardiovascular disease (15%). An increasing mortality trend across the state was observed, with a higher increase in the countryside. An active spatiotemporal cluster of mortality comprising the metropolitan area and neighbouring cities was identified. The trend of COVID-19 mortality in Sergipe was increasing and the spatial distribution of deaths was heterogeneous with progression towards the countryside. Therefore, the use of spatial analysis techniques may contribute to surveillance and control of COVID-19 pandemic.

Despite high exposure to Middle East respiratory syndrome coronavirus (MERS-CoV), the predictors for seropositivity in the context of husbandry practices for camels in Eastern Africa are not well understood. We conducted a cross-sectional survey to describe the camel herd profile and determine the factors associated with MERS-CoV seropositivity in Northern Kenya. We enrolled 29 camel-owning households and administered questionnaires to collect herd and household data. Serum samples collected from 493 randomly selected camels were tested for anti-MERS-CoV antibodies using a microneutralisation assay, and regression analysis used to correlate herd and household characteristics with camel seropositivity. Households reared camels (median = 23 camels and IQR 16–56), and at least one other livestock species in two distinct herds; a home herd kept near homesteads, and a range/fora herd that resided far from the homestead. The overall MERS-CoV IgG seropositivity was 76.3%, with no statistically significant difference between home and fora herds. Significant predictors for seropositivity (P ⩽ 0.05) included camels 6–10 years old (aOR 2.3, 95% CI 1.0–5.2), herds with ⩾25 camels (aOR 2.0, 95% CI 1.2–3.4) and camels from Gabra community (aOR 2.3, 95% CI 1.2–4.2). These results suggest high levels of virus transmission among camels, with potential for human infection.

The epidemic of coronavirus disease 2019 (COVID-19) began in China and had spread rapidly to many other countries. This study aimed to identify risk factors associated with delayed negative conversion of SARS-CoV-2 in COVID-19 patients. In this retrospective single-centre study, we included 169 consecutive patients with confirmed COVID-19 in Zhongnan Hospital of Wuhan University from 15th January to 2nd March. The cases were divided into two groups according to the median time of SARS-CoV-2 negative conversion. The differences between groups were compared. In total, 169 patients had a median virus negative conversion time of 18 days (interquartile range: 11–25) from symptom onset. Compared with the patients with short-term negative conversion, those with long-term conversion had an older age, higher incidence of comorbidities, chief complaints of cough and chest distress/breath shortness and severer illness on admission, higher level of leucocytes, neutrophils, aspartate aminotransferase, creatine kinase and erythrocyte sedimentation rate (ESR), lower level of CD3+CD4+ lymphocytes and albumin and more likely to receive mechanical ventilation. In multivariate analysis, cough, leucocytes, neutrophils and ESR were positively correlated with delayed virus negative conversion, and CD3+CD4+ lymphocytes were negatively correlated. The integrated indicator of leucocytes, neutrophils and CD3+CD4+ lymphocytes showed a good performance in predicting the negative conversion within 2 weeks (area under ROC curve (AUC) = 0.815), 3 weeks (AUC = 0.804), 4 weeks (AUC = 0.812) and 5 weeks (AUC = 0.786). In conclusion, longer quarantine periods might be more justified for COVID-19 patients with cough, higher levels of leucocytes, neutrophils and ESR and lower levels of CD3+CD4+ lymphocytes.

Ten porcine enteroviruses, 2 porcine adenoviruses and 1 coronavirus were isolated directly from 32 samples ofslurry collected from a pig fattening house. Concentration of the same samples by adsorption with the polyelectrolyte PE-60 yielded 24 porcine enteroviruses and 3 porcine adenoviruses. A porcine enterovirus was isolated, following PE-60 concentration, from 1 of 6 slurry samples from a sow farrowing house. No virus was isolated from 12 samples of slurry from dairy cows nor from 6 slurry samples from a calf-rearing unit. A porcine enterovirus was isolated from soil samples, after concentration with PE-60, collected 1, 2 and 8 days after pig slurry was spread on hay stubble. Two porcine enteroviruses were isolated by membrane filtration from 26 samples of surface run-off from land on which pig slurry was routinely spread, and 2 bovine enteroviruses were isolated from cattle feedlot run-off after adsorption to layers of talc and celite followed by hydroextraction. A porcine enterovirus was also isolated from 1 of 33 samples of surface water collected on farms on which pig slurry was routinely spread on the land, but no virus was isolated from 36 samples of ground water from the same farms. The surface water and ground water samples were concentrated by talc-celite adsorption and hydroextraction.

Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (Rt) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.

Using a stochastic model, we assess the risk of importation-induced local transmission chains in locations seeing few or no local transmissions and evaluate the role of quarantine in the mitigation of this risk. We find that the rate of importations plays a critical role in determining the risk that case importations lead to local transmission chains, more so than local transmission characteristics, i.e. strength of social distancing measures (NPI). The latter influences the severity of the outbreaks when they do take place. Quarantine after arrival in a location is an efficacious way to reduce the rate of importations. Locations that see no or low-level local transmission should ensure that the rate of importations remains low. A high level of compliance with post-arrival quarantine followed by testing achieves this objective with less of an impact than travel restrictions or bans.

The prevalence of asymptomatic infection by coronavirus disease 2019 (COVID-19) as a critical measure for effectiveness of mitigation strategy has been reported to be widely varied. In this study, we aimed to determine the prevalence of asymptomatic infection using serosurvey on general population. In a cross-sectional seroprevalence survey in Guilan province, Iran, the specific antibody against COVID-19 in a representative sample was detected using rapid test kits. Among 117 seropositive subjects, prevalence of asymptomatic infection was determined based on the history of symptoms during the preceding 3 months. The design-adjusted prevalence of asymptomatic infection was 57.2% (95% confidence interval (CI) 44–69). The prevalence was significantly lower in subjects with previous contacts to COVID-19 patients (12%, 95% CI 2–49) than others without (69%, 95% CI, 46–86). The lowest prevalence was for painful body symptom (74.4%). This study revealed that more than half of the infected COVID-19 patients had no symptoms. The implications of our findings include the importance of adopting public health measures such as social distancing and inefficiency of contact tracing to interrupt epidemic transmission.

The epidemiological target of lockdowns is to drive down the effective reproduction number (Rt) to less than 1. A key unknown is the duration that lockdowns need to be in place to achieve this and which lockdown measures are effective. Daily number of laboratory confirmed community coronavirus 2019 cases were extracted from regular reports from the Ministry of Health Singapore from 20 March 2020 to 4 May 2020. We generated daily Rt to estimate the time needed for these public health lockdown measures to control the spread of severe acute respiratory syndrome coronavirus 2 as demonstrated by Rt < 1. It took about 14 days of nationwide lockdown for the Rt trend to change and start falling. The upper limit of the 95% confidence interval for time to Rt < 1 was day 15 of lockdown. We have shown that it is possible to start ‘bending the Rt curve’ about 2 weeks after implementation of specific lockdown measures with strict compliance.

This study investigated the morbidity associated with respiratory virus infections in patients with well-documented chest disease, and the risk of transmission between close contacts. Patients informed the study team if they were exposed to a family member or colleague with a cold. Patients and symptomatic index cases recorded respiratory symptoms during the study period. Acute nasopharyngeal swabs and paired sera were obtained for viral diagnosis.

Twenty-five (43%) of 58 recorded exposures resulted in a symptomatic illness and 16 (28%) patients developed lower respiratory tract symptoms. Sixteen (64%) of the 25 symptomatic patients contacted their general practitioner, 14 (56%) received antibiotics and 4 (16%) were hospitalized. Mean duration of illness was 10·6 days in symptomatic patients and 5·7 days in their corresponding index cases (P < 0·005). Mean symptom scores were 100·6 in symptomatic patients and 62.2 in index cases (P < 0·01). Respiratory viruses were identified in 19 (33%) episodes. Rhinovirus, coronavirus and respiratory syncytial virus infections were all associated with lower respiratory tract exacerbations.

Respiratory tract symptoms following exposure to a cold were comparatively severe in these patients with chronic chest disease. This group of patients might gain particular benefit from the introduction of effective vaccines or antiviral therapy.

A 2-year study from January 1981 to December 1982 was undertaken to determine the role of viruses in the causation of diarrhoea in hospitalized children in Pune, Maharashtra State, India. The stool samples of 426 children (213 diarrhoeal and 213 non-diarrhoeal controls) were investigated by electron microscopy and ELISA for the presence of viruses. Six morphologically distinct viruses were visualized: rotavirus, coronavirus-like particles (CVLP), adenovirus, astrovirus, calicivirus and small round virus-like particles (SRV). Rotavirus was detected in 28·6% of the diarrhoea! patients and in 1·4 % of the controls. The frequency of infection with rotavirus was highest in the children aged less than 5 years. The mean age of rotavirus-positive patients was 11 months. Although rotavirus was detected in almost every month, there has a seasonal trend for colder months when CVLP cases were fewest. However, the prevalence of CVLP was greater in the control group (23–0%) rather than in those with diarrhoea (8–9%). In the control group, CVLP were detected more frequently during the summer months. An inverse relationship between CVLP and rotavirus was observed in children. Adenovirus, astrovirus, calicivirus and SRV were detected in a small proportion of children with and without clinical symptoms of gastroenteritis.

After preliminary trials, the detailed changes in the concentration of specific circulating and local antibodies were followed in 15 volunteers inoculated with coronavirus 229E. Ten of them, who had significantly lower concentrations of pre-existing antibody than the rest, became infected and eight of these developed colds. A limited investigation of circulating lymphocyte populations showed some lymphocytopenia in infected volunteers. In this group, antibody concentrations started to increase 1 week after inoculation and reached a maximum about 1 week later. Thereafter antibody titres slowly declined. Although concentrations were still slightly raised 1 year later, this did not always prevent reinfection when volunteers were then challenged with the homologous virus. However, the period of virus shedding was shorter than before and none developed a cold. All of the uninfected group were infected on re-challenge although they also appeared to show some resistance to disease and in the extent of infection. These results are discussed with reference to natural infections with coronavirus and with other infections, such as rhinovirus infections.

Although Middle East respiratory syndrome coronavirus (MERS-CoV) has a recorded 5 years of circulation in 27 countries worldwide, there is no international study to assess whether there is variation in mortality by region. Neither has there been a comprehensive study detailing how the disease characteristics of MERS-CoV influence mortality in patients presenting symptoms. This study aimed to assess how region, patient and disease characteristics influence 14- and 45-day mortality in MERS patients. The author utilised publically available data on MERS-CoV. The study included 883 MERS patients reported between 5 January 2015 and 10 March 2017. Data on patient and disease characteristics were collected. The mean age at MERS-CoV diagnosis was 54.3 years: 69.1% were male, and 86.7% of the cases were reported from Saudi Arabia. About 40% of MERS patients studied were over the age of 60. The study estimated 14- and 45-day survival rates after initial onset of symptoms: 83.67% and 65.9%, respectively. Saudi Arabian MERS patients exhibited 4.1 and 5.0 times higher 14-day (adjusted hazard risk (aHR) = 4.1; 95% confidence interval (CI) 1.012–16.921) and 45-day (aHR = 5.0; 95% CI 1.856–13.581) mortality risk compared with MERS patients in the Republic of Korea or other countries. Similarly, Middle Eastern MERS patients showed 5.3 and 4.1 times higher 14-day (aHR = 5.3; 95% CI 1.070–25.902) and 45-day (aHR = 4.1; 95% CI 1.288–113.076) mortality risk compared with MERS patients in the Republic of Korea or other countries. The results demonstrated a link between mortality and geography, disease and patient factors such as regions, symptoms, source of infections, underlying medical conditions, modes of transmission, non-healthcare workers and those of older age. Educational programmes, access to healthcare and early diagnosis could be implemented as modifiable factors to reduce the higher mortality rates in MERS patients.