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Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case.

ABSTRACT: The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. This is a Hidden Markov Model whose hidden layer is a regeneration process with Poisson immigration, Po-INAR(1), together with a mechanism that allows the estimation of the under-reporting in non-stationary count time series. A novelty of the model is that the expectation of the unobserved process's innovations is a time-dependent function defined in such a way that information about the spread of an epidemic, as modelled through a Susceptible-Infectious-Removed dynamical system, is incorporated into the model. In addition, the parameter controlling the intensity of the under-reporting is also made to vary with time to adjust to possible seasonality or trend in the data. Maximum likelihood methods are used to estimate the parameters of the model.

SUBMITTER: Fernandez-Fontelo A

PROVIDER: S-EPMC7714127 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case.

Fernández-Fontelo Amanda A Moriña David D Cabaña Alejandra A Arratia Argimiro A Puig Pere P

PloS one 20201203 12

The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. This is a Hidden Markov Model whose hidden layer is a regeneration process with Poisson immigration, Po-INAR(1), together with a mechanism that allows the estimation of the under-reporting in non-stationary count time series. A novelty of the model is that the expectation of the unobserved process's innovations is a time-dependent f ...[more]

PMID: 33270713

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Project description:Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale non-pharmaceutical interventions (NPIs) were implemented as national emergencies in most of the country's municipalities, starting with a lockdown on March 20th, 2020. Recently, approaches that combine movement data (measured as the number of commuters between units), metapopulation models to describe disease dynamics subdividing the population into Susceptible-Exposed-Asymptomatic-Infected-Recovered-Diseased and statistical inference algorithms have been pointed as a practical approach to both nowcast and forecast the number of cases and deaths. We used an iterated filtering (IF) framework to estimate the model transmission parameters using the reported data across 281 municipalities from March to late October in locations with more than 50 reported deaths and cases in Colombia. Since the model is high dimensional (6 state variables in every municipality), inference on those parameters is highly non-trivial, so we used an Ensemble-Adjustment-Kalman-Filter (EAKF) to estimate time variable system states and parameters. Our results show the model's ability to capture the characteristics of the outbreak in the country and provide estimates of the epidemiological parameters in time at the national level. Importantly, these estimates could become the base for planning future interventions as well as evaluating the impact of NPIs on the effective reproduction number ([Formula: see text]) and the critical epidemiological parameters, such as the contact rate or the reporting rate. However, our forecast presents some inconsistency as it overestimates the deaths for some locations as Medellín. Nevertheless, our approach demonstrates that real-time, publicly available ensemble forecasts can provide short-term predictions of reported COVID-19 deaths in Colombia. Therefore, this model can be used as a forecasting tool to evaluate disease dynamics and aid policymakers in infectious outbreak management and control.

Project description:The new corona virus infection SARS-CoV2 which was later renamed COVID-19 is a pandemic affecting public health. The fear and the constraints imposed to control the pandemic may correspondingly influence leisure activities, such as birding, which is the practice of observing birds based on visual and acoustic cues. Birders are people who carry out birding observations around the globe and contribute to the massive data collection in citizen science projects. Contrasting to earlier COVID-19 studies, which have concentrated on clinical, pathological, and virological topics, this study focused on the behavioral changes of birders. A total of 4484 questionnaire survey responses from 97 countries were received. The questionnaire had an open-ended style. About 85% of respondents reported that COVID-19 has changed their birding behavior. The most significant change in birdwatchers' behavior was related to the geographic coverage of birding activities, which became more local. People focused mostly on yard birding. In total, 12% of respondents (n = 542 cases) reported having more time for birding, whereas 8% (n = 356 cases) reported having less time for birding. Social interactions decreased since respondents, especially older people, changed their birding behavior toward birding alone or with their spouse. Women reported more often than men that they changed to birding alone or with their spouse, and women also reported more often about canceled fieldtrips or society meetings. Respondents from higher developed countries reported that they spend currently more time for birding, especially for birding alone or with their spouse, and birding at local hotspots. Our study suggests that long lockdowns with strict regulations may severely impact on leisure activities. In addition, a temporal and spatial shift in birding due to the pandemic may influence data quality in citizen science projects. As nature-based recreation will be directed more toward nearby sites, environmental management resources and actions need to be directed to sites that are located near the users, e.g., in urban and suburban areas. The results can be applied with caution to other nature-based recreational activities.

Project description:BackgroundThe aim of this study was to assess the disease burden of the 2009 pandemic influenza A(H1N1) in Greece.Methodology/principal findingsData on influenza-like illness (ILI), collected through cross-sectional nationwide telephone surveys of 1,000 households in Greece repeated for 25 consecutive weeks, were combined with data from H1N1 virologic surveillance to estimate the incidence and the clinical attack rate (CAR) of influenza A(H1N1). Alternative definitions of ILI (cough or sore throat and fever>38°C [ILI-38] or fever 37.1-38°C [ILI-37]) were used to estimate the number of symptomatic infections. The infection attack rate (IAR) was approximated using estimates from published studies on the frequency of fever in infected individuals. Data on H1N1 morbidity and mortality were used to estimate ICU admission and case fatality (CFR) rates. The epidemic peaked on week 48/2009 with approximately 750-1,500 new cases/100,000 population per week, depending on ILI-38 or ILI-37 case definition, respectively. By week 6/2010, 7.1%-15.6% of the population in Greece was estimated to be symptomatically infected with H1N1. Children 5-19 years represented the most affected population group (CAR:27%-54%), whereas individuals older than 64 years were the least affected (CAR:0.6%-2.2%). The IAR (95% CI) of influenza A(H1N1) was estimated to be 19.7% (13.3%, 26.1%). Per 1,000 symptomatic cases, based on ILI-38 case definition, 416 attended health services, 108 visited hospital emergency departments and 15 were admitted to hospitals. ICU admission rate and CFR were 37 and 17.5 per 100,000 symptomatic cases or 13.4 and 6.3 per 100,000 infections, respectively.Conclusions/significanceInfluenza A(H1N1) infected one fifth and caused symptomatic infection in up to 15% of the Greek population. Although individuals older than 65 years were the least affected age group in terms of attack rate, they had 55 and 185 times higher risk of ICU admission and CFR, respectively.

Project description:BackgroundOver the past few decades, economic, political, and social changes have directly and indirectly affected the health of the Mongolian population. To date, no comprehensive analysis has been conducted on the burden of diseases in this country. Thus, we aimed to describe the leading causes of death and disabling conditions and their trends between 1990 and 2019 in the Mongolian population.MethodsWe used the data from the Global Burden of Disease (GBD) 2019 study. In the current study, we examined life expectancy at birth, healthy life expectancy, the 20 leading causes of death, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted-life-years (DALYs), and the contribution of major risk factors to DALYs in Mongolia.FindingsThe life expectancy at birth in Mongolia has gradually increased since 1995 and reached 63.8 years for men and 72.7 for women in 2019. The highest increase in the age-standardised death rate between 1990 and 2019 occurred in alcohol use disorders (628.6%; 95% UI 10.0-1109.6) among men, and in liver cancer (129.1%; UI 65.3-222.4) among women. Ischaemic heart disease and stroke showed the highest rates of death, YLLs, and DALYs among both men and women. In 2019, the highest age-standardised rates of DALYs were attributable to high systolic blood pressure and dietary risks.InterpretationAlthough Mongolia saw substantial improvements across many communicable diseases, maternal and neonatal disorders, and under-5 mortality between 1990 and 2019, non-communicable diseases remained leading causes of mortality. The mortality from the most preventable causes such as injury, alcohol use, and dietary risks remain substantially high, suggesting that individual and social efforts are needed to tackle these diseases. Our analyses will support the development of policy priorities and action plans in multiple sectors to improve the overall health of the Mongolian population.FundingBill & Melinda Gates Foundation.

Dataset Information

Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case.

Publications

Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case.

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