Kolapo M Oyebola, Funmilayo C Ligali, Afolabi J Owoloye, Blessing D Erinwusi, Adesola Z Musa, Oluwagbemiga O Aina, Babatunde L Salako
{"title":"机器学习对尼日利亚COVID-19非药物干预措施有效性的见解。","authors":"Kolapo M Oyebola, Funmilayo C Ligali, Afolabi J Owoloye, Blessing D Erinwusi, Adesola Z Musa, Oluwagbemiga O Aina, Babatunde L Salako","doi":"10.1093/inthealth/ihae065","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The lack of effective pharmacological measures during the early phase of the COVID-19 pandemic prompted the implementation of non-pharmaceutical interventions (NPIs) as initial mitigation strategies. The impact of these NPIs on COVID-19 in Nigeria is not well-documented. This study sought to assess the effectiveness of NPIs to support future epidemic responses.</p><p><strong>Methods: </strong>Daily COVID-19 cases and deaths were analysed using smoothed variables to identify transmission trends. Regression analysis and clustering algorithms were applied to evaluate the impact of each NPI.</p><p><strong>Results: </strong>Multiple transmission peaks were reported, with the highest smoothed daily new cases (approximately 1790) observed around 29 December 2021 and smoothed daily new deaths (approximately 23) peaking around 8 September 2021. NPIs such as public transport (coefficient value -166.56, p=0.01) and workplace closures (coefficient value -150.06, p=0.01) strongly correlated with decreased case numbers. This finding highlights the importance of mobility control and non-essential workplace management in slowing infection transmission during an outbreak. Public transport restrictions (coefficient value -2.43, p<0.001) also had a direct effect on death reduction.</p><p><strong>Conclusions: </strong>Public transport restrictions and workplace closures correlated with reductions in the number of cases and deaths. These findings can guide future pandemic responses to enhance favourable public health outcomes.</p>","PeriodicalId":49060,"journal":{"name":"International Health","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine learning insights on the effectiveness of non-pharmaceutical interventions against COVID-19 in Nigeria.\",\"authors\":\"Kolapo M Oyebola, Funmilayo C Ligali, Afolabi J Owoloye, Blessing D Erinwusi, Adesola Z Musa, Oluwagbemiga O Aina, Babatunde L Salako\",\"doi\":\"10.1093/inthealth/ihae065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The lack of effective pharmacological measures during the early phase of the COVID-19 pandemic prompted the implementation of non-pharmaceutical interventions (NPIs) as initial mitigation strategies. The impact of these NPIs on COVID-19 in Nigeria is not well-documented. This study sought to assess the effectiveness of NPIs to support future epidemic responses.</p><p><strong>Methods: </strong>Daily COVID-19 cases and deaths were analysed using smoothed variables to identify transmission trends. Regression analysis and clustering algorithms were applied to evaluate the impact of each NPI.</p><p><strong>Results: </strong>Multiple transmission peaks were reported, with the highest smoothed daily new cases (approximately 1790) observed around 29 December 2021 and smoothed daily new deaths (approximately 23) peaking around 8 September 2021. NPIs such as public transport (coefficient value -166.56, p=0.01) and workplace closures (coefficient value -150.06, p=0.01) strongly correlated with decreased case numbers. This finding highlights the importance of mobility control and non-essential workplace management in slowing infection transmission during an outbreak. Public transport restrictions (coefficient value -2.43, p<0.001) also had a direct effect on death reduction.</p><p><strong>Conclusions: </strong>Public transport restrictions and workplace closures correlated with reductions in the number of cases and deaths. These findings can guide future pandemic responses to enhance favourable public health outcomes.</p>\",\"PeriodicalId\":49060,\"journal\":{\"name\":\"International Health\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-01-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/inthealth/ihae065\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/inthealth/ihae065","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Machine learning insights on the effectiveness of non-pharmaceutical interventions against COVID-19 in Nigeria.
Background: The lack of effective pharmacological measures during the early phase of the COVID-19 pandemic prompted the implementation of non-pharmaceutical interventions (NPIs) as initial mitigation strategies. The impact of these NPIs on COVID-19 in Nigeria is not well-documented. This study sought to assess the effectiveness of NPIs to support future epidemic responses.
Methods: Daily COVID-19 cases and deaths were analysed using smoothed variables to identify transmission trends. Regression analysis and clustering algorithms were applied to evaluate the impact of each NPI.
Results: Multiple transmission peaks were reported, with the highest smoothed daily new cases (approximately 1790) observed around 29 December 2021 and smoothed daily new deaths (approximately 23) peaking around 8 September 2021. NPIs such as public transport (coefficient value -166.56, p=0.01) and workplace closures (coefficient value -150.06, p=0.01) strongly correlated with decreased case numbers. This finding highlights the importance of mobility control and non-essential workplace management in slowing infection transmission during an outbreak. Public transport restrictions (coefficient value -2.43, p<0.001) also had a direct effect on death reduction.
Conclusions: Public transport restrictions and workplace closures correlated with reductions in the number of cases and deaths. These findings can guide future pandemic responses to enhance favourable public health outcomes.
期刊介绍：
International Health is an official journal of the Royal Society of Tropical Medicine and Hygiene. It publishes original, peer-reviewed articles and reviews on all aspects of global health including the social and economic aspects of communicable and non-communicable diseases, health systems research, policy and implementation, and the evaluation of disease control programmes and healthcare delivery solutions.
It aims to stimulate scientific and policy debate and provide a forum for analysis and opinion sharing for individuals and organisations engaged in all areas of global health.
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