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Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.

ABSTRACT: The ongoing outbreak of COVID-19 challenges the health systems and epidemiological responses of all countries worldwide. Although preventive measures have been globally considered, the spatial heterogeneity of its effectiveness is evident, underscoring global health inequalities. Using Bayesian-based Markov chain Monte Carlo simulations, we identify the spatial association of socioeconomic factors and the risk for dying from COVID-19 in Colombia. We confirm that from March 16 to October 04, 2020, the COVID-19 case-fatality rate and the multidimensional poverty index have a heterogeneous spatial distribution. Spatial analysis reveals that the risk of dying from COVID-19 increases in regions with a higher proportion of poor people with dwelling (RR 1.74 95%CI = 1.54-9.75), educational (RR 1.69 95%CI = 1.36-5.94), childhood/youth (RR 1.35 95%CI = 1.08-4.03), and health (RR 1.16 95%CI = 1.06-2.04) deprivations. These findings evidence the vulnerability of most disadvantaged members of society to dying in a pandemic and assist the spatial planning of preventive strategies focused on vulnerable communities.

SUBMITTER: Polo G

PROVIDER: S-EPMC8956344 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.

Polo Gina G Soler-Tovar Diego D Villamil Jimenez Luis Carlos LC Benavides-Ortiz Efraín E Mera Acosta Carlos C

Spatial and spatio-temporal epidemiology 20220325

The ongoing outbreak of COVID-19 challenges the health systems and epidemiological responses of all countries worldwide. Although preventive measures have been globally considered, the spatial heterogeneity of its effectiveness is evident, underscoring global health inequalities. Using Bayesian-based Markov chain Monte Carlo simulations, we identify the spatial association of socioeconomic factors and the risk for dying from COVID-19 in Colombia. We confirm that from March 16 to October 04, 2020 ...[more]

PMID: 35691638

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Project description:When the population risk factors and reporting systems are similar, the assessment of the case-fatality (or lethality) rate (ratio of cases to deaths) represents a perfect tool for analyzing, understanding and improving the overall efficiency of the health system. The objective of this article is to estimate the influence of the hospital care system on lethality in metropolitan France during the inception of the COVID-19 epidemic, by analyzing the spatial variability of the hospital case-fatality rate (CFR) between French districts. In theory, the hospital age-standardized CFR should not display significant differences between districts, since hospital lethality depends on the virulence of the pathogen (the SARS-CoV-2 virus), the vulnerability of the population (mainly age-related), the healthcare system quality, and cases and deaths definition and the recording accuracy. We analyzed hospital data on COVID-19 hospitalizations, severity (admission to intensive care units for reanimation or endotracheal intubation) and mortality, from March 19 to May 8 corresponding to the first French lockdown. All rates were age-standardized to eliminate differences in districts age structure. The results show that the higher case-fatality rates observed by districts are mostly related to the level of morbidity. Time analysis shows that the case-fatality rate has decreased over time, globally and in almost all districts, showing an improvement in the management of severe patients during the epidemic. In conclusion, it appears that during the first critical phase of COVID-19 ramping epidemic in metropolitan France, the higher case-fatality rates were generally related to the higher level of hospitalization, then potentially related to the overload of healthcare system. Also, low hospitalization with high case-fatality rates were mostly found in districts with low population density, and could due to some limitation of the local healthcare access. However, the magnitude of this increase of case-fatality rate represents less than 10 per cent of the average case-fatality rate, and this variation is small compared to much greater variation across countries reported in the literature.

Project description:BackgroundDuring the first wave of the COVID-19 pandemic a high case fatality rate (CFR) was noticed worldwide including also Germany where the first European cases have been observed. The WHO recommended immediate intubation for patients with dyspnoea which has since been revised after reviewing the initial clinical outcome. The objective of this study is to analyze CFR and assess if there is an advantage of a more conservative management of COVID-19 induced hypoxemia.MethodsPCR confirmed COVID-19 infections and death counts were obtained for all German districts from 27 Jan 2020 until 15 Feb 2021 using official reports of Robert Koch Institute Berlin, Germany. A moving average CFRt was constructed by dividing disease related deaths two weeks after a given index day by the number of infections two weeks prior to that date. In addition to a local comparison also mortality outcomes in other German speaking countries were compared.ResultsThe mean CFR is estimated to be 2.92% based on 71.965 fatalities and 2.465.407 cases. There was a large regional scattering of CFRs across the German districts. Differences of the mortality pattern were observed also at state level and preserved across different sex and age groups while being largely independent of case numbers. Although Munich city had higher infection rates, more patients died during the first wave in Hamburg (OR 1.6, 95% CI 1.3-1.9) which was mirrored also by higher death risk at Hamburg intensive care units (OR 2.0, 95% CI 1.3-3.1). While the majority of Munich hospitals favoured a conservative management of hypoxemia including high flow nasal cannula (HFNC), Hamburg hospitals followed a more aggressive scheme of early mechanical ventilation (MV). Austria and Switzerland experienced higher CFRs than Germany during the first wave but after changing their treatment guidelines, both countries experienced lower CFRs during the second wave.ConclusionUsing retrospective public health data, different case fatality rates have been observed across Germany. A more conservative management of COVID-19 induced Adult Respiratory Distress Syndrome (ARDS) is justified also by epidemiological data.

Project description:ObjectiveTo investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally.DesignPublicly available register-based ecological study.SettingTwo hundred and nine countries/territories in the world.ParticipantsAggregated data including 10 445 656 confirmed COVID-19 cases.Primary and secondary outcome measuresCOVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website.ResultsThe average of country/territory-specific COVID-19 CFR is about 2%-3% worldwide and higher than previously reported at 0.7%-1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR.ConclusionThe association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.

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Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.

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Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.

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