Using the COVID-19 to influenza ratio to estimate the numbers of symptomatic COVID-19 cases in Wuhan prior to the lockdown.
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ABSTRACT:
SUBMITTER: Du Z
PROVIDER: S-EPMC7276025 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPandemic SARS-CoV-2 was first reported in Wuhan, China on December 31, 2019. Twenty-one days later, the US identified its first case--a man who had traveled from Wuhan to the state of Washington. Recent studies in the Wuhan and Seattle metropolitan areas retrospectively tested samples taken from patients with COVID-like symptoms. In the Wuhan study, there were 4 SARS-CoV-2 positives and 7 influenza positives out of 26 adults outpatients who sought care for influenza-like-illness at two central hospitals prior to January 12, 2020. The Seattle study reported 25 SARS-CoV-2 positives and 442 influenza positives out of 2353 children and adults who reported acute respiratory illness prior to March 9, 2020. Here, we use these findings to extrapolate the early prevalence of symptomatic COVID-19 in Wuhan and Seattle.MethodsFor each city, we estimate the ratio of COVID-19 to influenza infections from the retrospective testing data and estimate the age-specific prevalence of influenza from surveillance reports during the same time period. Combining these, we approximate the total number of symptomatic COVID-19 infections.FindingsIn Wuhan, there were an estimated 1386 [95% CrI: 420-3793] symptomatic cases over 30 of COVID-19 between December 30, 2019 and January 12, 2020. In Seattle, we estimate that 2268 [95% CrI: 498, 6069] children under 18 and 4367 [95% CrI: 2776, 6526] adults were symptomatically infected between February 24 and March 9, 2020. We also find that the initial pandemic wave in Wuhan likely originated with a single infected case who developed symptoms sometime between October 26 and December 13, 2019; in Seattle, the seeding likely occurred between December 25, 2019 and January 15, 2020.InterpretationThe spread of COVID-19 in Wuhan and Seattle was far more extensive than initially reported. The virus likely spread for months in Wuhan before the lockdown. Given that COVID-19 appears to be overwhelmingly mild in children, our high estimate for symptomatic pediatric cases in Seattle suggests that there may have been thousands more mild cases at the time.
| S-EPMC7422814 | biostudies-literature
Project description:On 8 April 2020, the Chinese government lifted the lockdown and opened up public transportation in Wuhan, China, the epicentre of the COVID-19 pandemic. After 76 days in lockdown, Wuhan residents were allowed to travel outside of the city and go back to work. Yet, given that there is still no vaccine for the virus, this leaves many doubting whether life will indeed go back to normal. The aim of this research was to track longitudinal changes in motivation for self-isolating, life-structured, indicators of well-being and mental health after lockdown was lifted. We have recruited 462 participants in Wuhan, China, prior to lockdown lift between 3 and 7 April 2020 (Time 1), and have followed up with 292 returning participants between 18 and 22 April 2020 (Time 2), 284 between 6 and 10 May 2020 (Time 3), and 279 between 25 and 29 May 2020 (Time 4). This four-wave study used latent growth models to examine how Wuhan residents' psychological experiences change (if at all) within the first two months after lockdown was lifted. The Stage 1 manuscript associated with this submission received in-principle acceptance (IPA) on 2 June 2020. Following IPA, the accepted Stage 1 version of the manuscript was preregistered on the OSF at https://osf.io/g2t3b. This preregistration was performed prior to data analysis. Generally, our study found that: (i) a majority of people still continue to value self-isolation after lockdown was lifted; (ii) by the end of lockdown, people perceived gradual return to normality and restored structure of everyday life; (iii) the psychological well-being slightly improved after lockdown was lifted; (iv) people who used problem solving and help-seeking as coping strategies during lockdown had better well-being and mental health by the end of the lockdown; (v) those who experienced more disruptions in daily life during lockdown would display more indicators of psychological ill-being by the end of the lockdown.
| S-EPMC7540789 | biostudies-literature
Project description:Here we document 47,381 individuals from 38 species, including 31 protected species sold between May 2017 and November 2019 in Wuhan's markets. We note that no pangolins (or bats) were traded, supporting reformed opinion that pangolins were not likely the spillover host at the source of the current coronavirus (COVID-19) pandemic. While we caution against the misattribution of COVID-19's origins, the wild animals on sale in Wuhan suffered poor welfare and hygiene conditions and we detail a range of other zoonotic infections they can potentially vector. Nevertheless, in a precautionary response to COVID-19, China's Ministries temporarily banned all wildlife trade on 26th Jan 2020 until the COVID-19 pandemic concludes, and permanently banned eating and trading terrestrial wild (non-livestock) animals for food on 24th Feb 2020. These interventions, intended to protect human health, redress previous trading and enforcement inconsistencies, and will have collateral benefits for global biodiversity conservation and animal welfare.
| S-EPMC8184983 | biostudies-literature
Project description:The COVID-19 pandemic has led to temporary changes in human-animal interactions due to changes in human activities. Here, we report on a surge in hedgehog observations during the first COVID-19 lockdown in Germany in 2020, on the citizen science Web portal "Igel in Bayern" (Hedgehogs in Bavaria) in Germany. This increase in comparison with previous years was attributed to an increase in the number of people reporting hedgehog observations, rather than an increase in the number of hedgehog observations made by each observer. Additionally, in contrast to other studies on the effects of a COVID-19 lockdown on observations recorded by citizen science projects, the share of observations made in more urbanized areas during the lockdown time was not higher than the change observed in less urbanized areas. This is possibly a result of the differences in COVID-19 measures between Germany and other countries where preceding studies were carried out, in particular the lack of measures limiting traveling outdoor activities for citizens.
| S-EPMC9204849 | biostudies-literature
Project description:Recent literature has reported a high percentage of asymptomatic or paucisymptomatic cases in subjects with COVID-19 infection. This proportion can be difficult to quantify; therefore, it constitutes a hidden population. This study aims to develop a proof-of-concept method for estimating the number of undocumented infections of COVID-19. This is the protocol for the INCIDENT (Hidden COVID-19 Cases Network Estimation) study, an online, cross-sectional survey with snowball sampling based on the network scale-up method (NSUM). The original personal network size estimation method was based on a fixed-effects maximum likelihood estimator. We propose an extension of previous Bayesian estimation methods to estimate the unknown network size using the Markov chain Monte Carlo algorithm. On 6 May 2020, 1963 questionnaires were collected, 1703 were completed except for the random questions, and 1652 were completed in all three sections. The algorithm was initialized at the first iteration and applied to the whole dataset. Knowing the number of asymptomatic COVID-19 cases is extremely important for reducing the spread of the virus. Our approach reduces the number of questions posed. This allows us to speed up the completion of the questionnaire with a subsequent reduction in the nonresponse rate.
| S-EPMC8198250 | biostudies-literature
Project description:Epidemiological models are widely used to analyze the spread of diseases such as the global COVID-19 pandemic caused by SARS-CoV-2. However, all models are based on simplifying assumptions and often on sparse data. This limits the reliability of parameter estimates and predictions. In this manuscript, we demonstrate the relevance of these limitations and the pitfalls associated with the use of overly simplistic models. We considered the data for the early phase of the COVID-19 outbreak in Wuhan, China, as an example, and perform parameter estimation, uncertainty analysis and model selection for a range of established epidemiological models. Amongst others, we employ Markov chain Monte Carlo sampling, parameter and prediction profile calculation algorithms. Our results show that parameter estimates and predictions obtained for several established models on the basis of reported case numbers can be subject to substantial uncertainty. More importantly, estimates were often unrealistic and the confidence/credibility intervals did not cover plausible values of critical parameters obtained using different approaches. These findings suggest, amongst others, that standard compartmental models can be overly simplistic and that the reported case numbers provide often insufficient information for obtaining reliable and realistic parameter values, and for forecasting the evolution of epidemics.
| S-EPMC7845523 | biostudies-literature
Project description:Highlights • Shared early 3 cases on ECMO application in severely ill COVID-19 patients• Revealed overall poor prognoses probably related to their age, underlying diseases, and COVID-19's evolution.• Proposedgrasping ecmo indications and selecting patients, especially during epidemic
| S-EPMC7489925 | biostudies-literature
Project description:The novel coronavirus (COVID-19) has induced unprecedented improvements of air quality due to drastic shrinking of human activities during the pandemic lockdown in 2020. While declines of most air pollutants have been globally evidenced in most cities worldwide, there is few detailed spatial knowledge at local scale. Therefore, we present here a high resolution mapping of the 2018-2020 evolution of human activities and air pollutants in Wuhan. Human activities were assessed by nighttime light radiance. We measured the air quality index (AQI) as the maximum value among air quality sub-indices of SO2, NO2, CO, O3 and particulate matter. We also compared mean monthly pollutant concentration during January-April in 2018, 2019 and 2020. Mapping results show that variations of nighttime light radiance were heterogenous at local scale, showing both rises and declines in the same district. The radiance decreased in eight districts located mostly in the city center, as a result of lower human activity, but the radiance increased in the five surrounding districts, as a consequence of people staying at home. AQI was low during lockdown, averaging at 57, but showed strong daily variations with a slight pollution around February 5 with AQI rising to 126. During this pollution event, particulate matter, SO2, NO2 and CO levels were positively correlated, suggesting common sources, but were not correlated with ozone; and particulate matter, SO2, NO2 and CO decreased with relative humidity, suggesting removal by precipitation. Comparison of 2020 data with previous years shows that particulate matter and NO2 were highly reduced, CO was less reduced due to ongoing power industries, SO2 first declined then increased to exceed 2018-19 values due to coal combustion, and ozone levels was more abundant due both to less NOx pollution and the weekend effect.Supplementary informationThe online version contains supplementary material available at 10.1007/s10311-021-01222-x.
| S-EPMC7986644 | biostudies-literature
Project description:Rationale: The global death toll from coronavirus disease (COVID-19) virus as of May 12, 2020, exceeds 286,000. The risk factors for death were attributed to advanced age and comorbidities but have not been accurately defined.Objectives: To report the clinical features of 85 fatal cases of COVID-19 in two hospitals in Wuhan.Methods: Medical records were collected of 85 fatal cases of COVID-19 between January 9, 2020, and February 15, 2020. Information recorded included medical history, exposure history, comorbidities, symptoms, signs, laboratory findings, computed tomographic scans, and clinical management.Measurements and Main Results: The median age of the patients was 65.8 years, and 72.9% were male. Common symptoms were fever (78 [91.8%]), shortness of breath (50 [58.8%]), fatigue (50 [58.8%]), and dyspnea (60 [70.6%]). Hypertension, diabetes, and coronary heart disease were the most common comorbidities. Notably, 81.2% of patients had very low eosinophil counts on admission. Complications included respiratory failure (80 [94.1%]), shock (69 [81.2%]), acute respiratory distress syndrome (63 [74.1%]), and arrhythmia (51 [60%]), among others. Most patients received antibiotic (77 [90.6%]), antiviral (78 [91.8%]), and glucocorticoid (65 [76.5%]) treatments. A total of 38 (44.7%) and 33 (38.8%) patients received intravenous immunoglobulin and IFN-α2b, respectively.Conclusions: In this depictive study of 85 fatal cases of COVID-19, most cases were males aged over 50 years with noncommunicable chronic diseases. The majority of the patients died of multiple organ failure. Early onset of shortness of breath may be used as an observational symptom for COVID-19 exacerbations. Eosinophilopenia may indicate a poor prognosis. A combination of antimicrobial drugs did not offer considerable benefit to the outcome of this group of patients.
| S-EPMC7258652 | biostudies-literature
Project description:Information about Parkinson's disease (PD) patients with severe COVID-19 is scarce. We aimed to analyze the clinical characteristics, outcomes, and risk factors affecting the prognosis of PD patients with severe COVID-19 infection. Clinical data of severe COVID-19 patients admitted at the Union Hospital, Wuhan between 28th January and 29th February 2020 were collected and analyzed. 10 patients (1.96%) had a medical history of PD with a mean (SD) age of 72.10 (± 11.46) years. The clinical characteristics and outcomes of severe COVID-19 with and without PD patients were then compared. There was no significant difference in overall mortality between the PD and non-PD patients with severe COVID-19 (p > 0.05). In PD patients with severe COVID-19, the proportion of patients with critical type, disturbance of consciousness, incidence of complications, white blood cells count and neutrophils counts on admission seem higher in the non-survivors. PD patients with older age, longer PD duration, and late stage PD may be highly susceptible to critical COVID-19 infection and bad outcome. The PD patients with consciousness disorders and complications that progressed rapidly are at increased risk of death.
| S-EPMC7779096 | biostudies-literature