Yufan Zheng , Keqi Yue , Eric W.M. Wong , Hsiang-Yu Yuan
{"title":"COVID-19 在香港流行期间,人类流动性和天气条件对登革热蚊子数量的影响","authors":"Yufan Zheng , Keqi Yue , Eric W.M. Wong , Hsiang-Yu Yuan","doi":"10.1016/j.idm.2025.04.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>While <em>Aedes</em> mosquitoes, the Dengue vectors, are expected to expand due to climate change, the impact of human mobility on them is largely unclear. Changes in human mobility, such as staying at home during the pandemic, likely affect mosquito abundance.</div></div><div><h3>Objectives</h3><div>We aimed to assess the influence of human mobility on the abundance and extensiveness of <em>Aedes albopictus</em>, taking account of the nonlinear lagged effects of weather, during the COVID-19 pandemic in Hong Kong.</div></div><div><h3>Methods</h3><div>Google human mobility indices (including residential, parks, and workplaces) and weather conditions (total rainfall and mean temperature) along with <em>Aedes albopictus</em> abundance and extensiveness, monitored using Gravidtrap were collected between April 2020 and August 2022. Distributed lag non-linear models with mixed-effects models were used to explore their influence in three areas of Hong Kong.</div></div><div><h3>Results</h3><div>Time spent at home (i.e., residential mobility) was negatively associated with mosquito abundance. The model projected that if residential mobility in 2022 was returned to the pre-pandemic level, the mosquito abundance would increase by an average of 80.49 % compared to actual observation. The relative risk (RR) of mosquito abundance was associated with low rainfall (<50 mm) after 4.5 months, peaking at 1.73, compared with 300 mm. Heavy rainfall (>500 mm) within 3 months was also associated with a peak RR of 1.41. Warm conditions (21–30 °C, compared with 20 °C) were associated with a higher RR of 1.47 after half a month.</div></div><div><h3>Discussion</h3><div>Human mobility is a critical factor along with weather conditions in mosquito prediction, and a stay-at-home policy may be an effective intervention to control <em>Aedes albopictus</em>.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 3","pages":"Pages 840-849"},"PeriodicalIF":8.8000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of human mobility and weather conditions on Dengue mosquito abundance during the COVID-19 pandemic in Hong Kong\",\"authors\":\"Yufan Zheng , Keqi Yue , Eric W.M. Wong , Hsiang-Yu Yuan\",\"doi\":\"10.1016/j.idm.2025.04.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>While <em>Aedes</em> mosquitoes, the Dengue vectors, are expected to expand due to climate change, the impact of human mobility on them is largely unclear. Changes in human mobility, such as staying at home during the pandemic, likely affect mosquito abundance.</div></div><div><h3>Objectives</h3><div>We aimed to assess the influence of human mobility on the abundance and extensiveness of <em>Aedes albopictus</em>, taking account of the nonlinear lagged effects of weather, during the COVID-19 pandemic in Hong Kong.</div></div><div><h3>Methods</h3><div>Google human mobility indices (including residential, parks, and workplaces) and weather conditions (total rainfall and mean temperature) along with <em>Aedes albopictus</em> abundance and extensiveness, monitored using Gravidtrap were collected between April 2020 and August 2022. Distributed lag non-linear models with mixed-effects models were used to explore their influence in three areas of Hong Kong.</div></div><div><h3>Results</h3><div>Time spent at home (i.e., residential mobility) was negatively associated with mosquito abundance. The model projected that if residential mobility in 2022 was returned to the pre-pandemic level, the mosquito abundance would increase by an average of 80.49 % compared to actual observation. The relative risk (RR) of mosquito abundance was associated with low rainfall (<50 mm) after 4.5 months, peaking at 1.73, compared with 300 mm. Heavy rainfall (>500 mm) within 3 months was also associated with a peak RR of 1.41. Warm conditions (21–30 °C, compared with 20 °C) were associated with a higher RR of 1.47 after half a month.</div></div><div><h3>Discussion</h3><div>Human mobility is a critical factor along with weather conditions in mosquito prediction, and a stay-at-home policy may be an effective intervention to control <em>Aedes albopictus</em>.</div></div>\",\"PeriodicalId\":36831,\"journal\":{\"name\":\"Infectious Disease Modelling\",\"volume\":\"10 3\",\"pages\":\"Pages 840-849\"},\"PeriodicalIF\":8.8000,\"publicationDate\":\"2025-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Disease Modelling\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468042725000284\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042725000284","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Impact of human mobility and weather conditions on Dengue mosquito abundance during the COVID-19 pandemic in Hong Kong
Background
While Aedes mosquitoes, the Dengue vectors, are expected to expand due to climate change, the impact of human mobility on them is largely unclear. Changes in human mobility, such as staying at home during the pandemic, likely affect mosquito abundance.
Objectives
We aimed to assess the influence of human mobility on the abundance and extensiveness of Aedes albopictus, taking account of the nonlinear lagged effects of weather, during the COVID-19 pandemic in Hong Kong.
Methods
Google human mobility indices (including residential, parks, and workplaces) and weather conditions (total rainfall and mean temperature) along with Aedes albopictus abundance and extensiveness, monitored using Gravidtrap were collected between April 2020 and August 2022. Distributed lag non-linear models with mixed-effects models were used to explore their influence in three areas of Hong Kong.
Results
Time spent at home (i.e., residential mobility) was negatively associated with mosquito abundance. The model projected that if residential mobility in 2022 was returned to the pre-pandemic level, the mosquito abundance would increase by an average of 80.49 % compared to actual observation. The relative risk (RR) of mosquito abundance was associated with low rainfall (<50 mm) after 4.5 months, peaking at 1.73, compared with 300 mm. Heavy rainfall (>500 mm) within 3 months was also associated with a peak RR of 1.41. Warm conditions (21–30 °C, compared with 20 °C) were associated with a higher RR of 1.47 after half a month.
Discussion
Human mobility is a critical factor along with weather conditions in mosquito prediction, and a stay-at-home policy may be an effective intervention to control Aedes albopictus.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.