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Estimating the COVID-19 infection rate: Anatomy of an inference problem.

ABSTRACT: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that, assuming accurate reporting of deaths, the infection fatality rates in Illinois, New York, and Italy are substantially lower than reported.

SUBMITTER: Manski CF

PROVIDER: S-EPMC7200382 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Estimating the COVID-19 infection rate: Anatomy of an inference problem.

Manski Charles F CF Molinari Francesca F

Journal of econometrics 20200506 1

As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of boundin ...[more]

PMID: 32377030

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Project description:BackgroundThe ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries.MethodsWe fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries.ResultsWe simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.ConclusionsThis study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.

Project description:BackgroundUnderstanding the risks associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission during oral health care delivery and assessing mitigation strategies for dental offices are critical to improving patient safety and access to oral health care.MethodsThe authors invited licensed US dentists practicing primarily in private practice or public health to participate in a web-based survey in June 2020. Dentists from every US state (n = 2,195) answered questions about COVID-19-associated symptoms, SARS-CoV-2 infection, mental and physical health conditions, and infection control procedures used in their primary dental practices.ResultsMost of the dentists (82.2%) were asymptomatic for 1 month before administration of the survey; 16.6% reported being tested for SARS-CoV-2; and 3.7%, 2.7%, and 0% tested positive via respiratory, blood, and salivary samples, respectively. Among those not tested, 0.3% received a probable COVID-19 diagnosis from a physician. In all, 20 of the 2,195 respondents had been infected with SARS-CoV-2; weighted according to age and location to approximate all US dentists, 0.9% (95% confidence interval, 0.5 to 1.5) had confirmed or probable COVID-19. Dentists reported symptoms of depression (8.6%) and anxiety (19.5%). Enhanced infection control procedures were implemented in 99.7% of dentists' primary practices, most commonly disinfection, COVID-19 screening, social distancing, and wearing face masks. Most practicing dentists (72.8%) used personal protective equipment according to interim guidance from the Centers for Disease Control and Prevention.ConclusionsCOVID-19 prevalence and testing positivity rates were low among practicing US dentists. This indicates that the current infection control recommendations may be sufficient to prevent infection in dental settings.Practical implicationsDentists have enhanced their infection control practices in response to COVID-19 and may benefit from greater availability of personal protective equipment. ClinicalTrials.gov: NCT04423770.

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Estimating the COVID-19 infection rate: Anatomy of an inference problem.

Publications

Estimating the COVID-19 infection rate: Anatomy of an inference problem.

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