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Coronavirus infections and deaths by poverty status: The effects of social distancing.

ABSTRACT: We study the spread of COVID-19 infections and deaths by county poverty level in the US. In the beginning of the pandemic, counties with either very low poverty levels or very high poverty levels reported the highest numbers of cases. A U-shaped relationship prevails for counties with high population density while among counties with low population density, only poorer counties report high incidence rates of COVID-19. Second, we discuss the pattern of infections spreading from higher to lower income counties. Third, we show that stay-at-home mandates caused significantly higher reductions in mobility in high income counties that experienced adverse weather shocks than counties that did not. These effects are not present in counties with high poverty rates. Using weather shocks in combination with stay-at-home mandates as an instrument for social distancing, we find that measures taken to promote social distancing helped curb infections in high income counties but not in low income counties. These results have important policy implications for containing the spread of infectious diseases in the future.

SUBMITTER: Jung J

PROVIDER: S-EPMC7756168 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo measure the effect of social distancing on reducing daily deaths, infections and hospital resources needed for coronavirus disease 2019 (COVID-19) patients during the first wave of the pandemic in Nordic countries.MethodsThe observations of social distancing, daily deaths, infections along with the needed hospital resources for COVID-19 patient hospitalizations including the numbers of all hospital beds, beds needed in ICUs and infection wards, nursing staffs needed in ICUs and infection wards were collected from the Institute for Health Metrics and Evaluation (IHME) by the University of Washington. The observations of social distancing were based on the reduction in human contact relative to background levels for each location quantified by cell phone mobility data collected from IHME. The weighted data per 100,000 population gathered in a 40-day period of the first wave of the pandemic in Denmark, Finland, Iceland, Norway and Sweden. Statistical technique of panel data analysis is used to measure the associations between social distancing and COVID-19 indicators in long-run.ResultsResults of dynamic long-run models confirm that a 1% rise in social distancing by reducing human contacts may decline daily deaths, daily infections, all hospital beds needed, beds/nurses needed in ICUs and beds/nurses needed in infection wards due COVID-19 pandemic by 1.13%, 15.26%, 1.10%, 1.17% and 1.89%, respectively. Moreover, results of error correction models verify that if the equilibriums between these series are disrupted by a sudden change in social distancing, the lengths of restoring back to equilibrium are 67, 62, 40, 22 and 49 days for daily deaths, daily infections, all hospital beds needed, nurses/beds needed in ICUs and nurses/beds needed in infection wards, respectively.ConclusionProper social distancing was a successful policy for tackling COVID-19 with falling mortality and infection rates as well as the needed hospital resources for patient hospitalizations in Nordic countries. The results alert governments of the need for continuously implementing social distancing policies while using vaccines to prevent national lockdowns and reduce the burden of patient hospitalizations.

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Coronavirus infections and deaths by poverty status: The effects of social distancing.

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