Evidence map›Paper›PMID 35527010›Full record

ArticleEnvironmental health and preventive medicine2022

Number of public health nurses and COVID-19 incidence rate by variant type: an ecological study of 47 prefectures in Japan.

Kimiko Tomioka, Midori Shima, Keigo Saeki

Abstract read
In one paragraph

Article in Environmental health and preventive medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  4. Detection of outlier prefectures on the mortality due to COVID-19 in Japan.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2023
    Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Kimiko TomiokaNara Prefectural Health Research Center, Nara Medical University.ORCID 0000-0002-9471-6987
Midori ShimaNara Prefectural Health Research Center, Nara Medical University.
Keigo SaekiNara Prefectural Health Research Center, Nara Medical University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunity health activities by public health nurses (PHNs) are known to improve lifestyle habits of local residents, and may encourage the practice of infectious disease prevention behaviors during the COVID-19 pandemic. We investigated the association between prefecture-level COVID-19 incidence rate and the number of PHNs per population in Japan, by the COVID-19 variant type.

methodsOur data were based on government surveys where prefectural-level data are accessible to the public. The outcome variable was the COVID-19 incidence rate (i.e., the cumulative number of COVID-19 cases per 100,000 population for each variant type in 47 prefectures). The explanatory variable was the number of PHNs per 100,000 population by prefecture. Covariates included socioeconomic factors, regional characteristics, healthcare resources, and health behaviors. The generalized estimating equations of the multivariable Poisson regression models were used to estimate adjusted incidence rate ratio (IRR) and 95% confidence interval (CI) for the COVID-19 cases. We performed stratified analyses by variant type (i.e., wild type, alpha variant, and delta variant).

resultsA total of 1,705,224 confirmed COVID-19 cases (1351.6 per 100,000 population) in Japan were reported as of September 30, 2021. The number of PHNs per 100,000 population in Japan was 41.9. Multivariable Poisson regression models showed that a lower number of PHNs per population was associated with higher IRR of COVID-19. Among all COVID-19 cases, compared to the highest quintile group of the number of PHNs per population, the adjusted IRR of the lowest quintile group was consistently significant in the models adjusting for socioeconomic factors (IRR: 3.76, 95% CI: 2.55-5.54), regional characteristics (1.73, 1.28-2.34), healthcare resources (3.88, 2.45-6.16), and health behaviors (2.17, 1.39-3.37). These significant associations were unaffected by the variant type of COVID-19.

conclusionWe found that the COVID-19 incidence rate was higher in prefectures with fewer PHNs per population, regardless of the COVID-19 variant type. By increasing the number of PHNs, it may be possible to contain the spread of COVID-19 in Japan and provide an effective human resource to combat emerging infectious diseases in the future.

Indexed as

COVID-19Nurses, Public HealthHumansIncidenceJapanPandemicsSARS-CoV-2COVID-19Ecological studiesIncidenceJapanPublic health nurse

Identifiers

PMID35527010
PMCPMC9251616

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.