Using location history data from cell phones of infectious patients for disease surveillance
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/9/9142/tde-11032024-154311/ |
Resumo: | Infectious diseases significantly contribute to global morbidity and mortality, highlighting the critical need for robust disease surveillance systems. The rapid and accurate identification of infection hotspots is crucial for effective disease control and eliminating vector reservoirs. Traditional methods, reliant on patient-reported data, are vague, slow, and non-integrative, presenting substantial barriers to fully understanding the underlying causes of infection transmission. The widespread usage of smartphones presents a unique opportunity to access, analyze, and monitor digital data. Particularly, location data can offer potential insights into infectious disease dynamics, which has remained largely unexplored. Firstly, the present study leverages location history data from smartphones of malaria patients in Manaus, Amazonas region, to pinpoint mosquito-breeding sites. Upon quantifying the location data, the primary transmission hotspots were identified to be concentrated on the outskirts of the city of Manaus. Additionally, the quantification and hotspot validation confirmed that newly visited locations during the exposure period were potential sources of infection transmission. Secondly, the current study also employs a novel digital contact investigation method for a human-to-human transmission infection such as tuberculosis to measure the exposure risk between the active index cases and their close contacts. The digital contact investigation revealed varied exposure durations between the recruited paired index and close contact participants based on the outcome of close contact. To summarize, the present study determines distinct mobility patterns associated with both these infectious diseases, potentially aiding in drafting targeted public health strategies and policies for digital epidemiological surveillance. |
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Using location history data from cell phones of infectious patients for disease surveillanceUsando dados do histórico de localização de telefones celulares de pacientes infecciosos para vigilância de doençasDigital epidemiologyDisease surveillanceEpidemiologia digitalGlobal positioning systemMalariaMaláriaSistema de posicionamento globalTuberculoseTuberculosisVigilância de doençasInfectious diseases significantly contribute to global morbidity and mortality, highlighting the critical need for robust disease surveillance systems. The rapid and accurate identification of infection hotspots is crucial for effective disease control and eliminating vector reservoirs. Traditional methods, reliant on patient-reported data, are vague, slow, and non-integrative, presenting substantial barriers to fully understanding the underlying causes of infection transmission. The widespread usage of smartphones presents a unique opportunity to access, analyze, and monitor digital data. Particularly, location data can offer potential insights into infectious disease dynamics, which has remained largely unexplored. Firstly, the present study leverages location history data from smartphones of malaria patients in Manaus, Amazonas region, to pinpoint mosquito-breeding sites. Upon quantifying the location data, the primary transmission hotspots were identified to be concentrated on the outskirts of the city of Manaus. Additionally, the quantification and hotspot validation confirmed that newly visited locations during the exposure period were potential sources of infection transmission. Secondly, the current study also employs a novel digital contact investigation method for a human-to-human transmission infection such as tuberculosis to measure the exposure risk between the active index cases and their close contacts. The digital contact investigation revealed varied exposure durations between the recruited paired index and close contact participants based on the outcome of close contact. To summarize, the present study determines distinct mobility patterns associated with both these infectious diseases, potentially aiding in drafting targeted public health strategies and policies for digital epidemiological surveillance.As doenças infecciosas são um dos principais contribuintes para a morbidade e a mortalidade globais, enfatizando a necessidade crítica de sistemas robustos de vigilância de doenças. A identificação rápida e precisa dos pontos críticos de infecção é fundamental para o controle eficaz de doenças e a eliminação de reservatórios de vetores. Os métodos tradicionais, que dependem de dados relatados por pacientes, são vagos, lentos e não integrativos, apresentando barreiras significativas para a compreensão total das causas subjacentes da transmissão de infecções. O uso generalizado de dispositivos móveis apresenta uma oportunidade única de acessar, analisar e monitorar dados digitais. Especialmente, dados de localização podem oferecer informações úteis sobre a dinâmica de doenças infecciosas, que permanecem em grande parte inexploradas. Primeiramente, o presente estudo utiliza dados de histórico de localização de smartphones de pacientes com malária em Manaus, na região do Amazonas, para identificar locais de reprodução de mosquitos. Ao quantificar os dados de localização, identificaram-se os principais pontos de transmissão concentrados nos arredores da cidade de Manaus. Além do mais, a quantificação e a validação em campo confirmaram que os locais recém-visitados durante o período de exposição eram potenciais fontes de transmissão da infecção. Em segundo lugar, o estudo atual também emprega um inovador método de investigação digital de contato para uma infecção por transmissão de humano para humano, como a tuberculose, a fim de medir o risco por exposição entre os casos índice ativos e seus contatos próximos. A investigação digital de contato revelou períodos de exposição variados entre os participantes recrutados em pares de casos índice e contatos próximos, com base no resultado do contato próximo. Em resumo, o presente estudo identifica padrões distintos de mobilidade associados a ambas essas doenças infecciosas, auxiliando potencialmente na elaboração de estratégias e políticas de saúde pública direcionadas para a vigilância epidemiológica digital.Biblioteca Digitais de Teses e Dissertações da USPNakaya, Helder Takashi ImotoGiddaluru, Jeevan2023-12-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/9/9142/tde-11032024-154311/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2024-05-03T19:25:02Zoai:teses.usp.br:tde-11032024-154311Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212024-05-03T19:25:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Using location history data from cell phones of infectious patients for disease surveillance Usando dados do histórico de localização de telefones celulares de pacientes infecciosos para vigilância de doenças |
title |
Using location history data from cell phones of infectious patients for disease surveillance |
spellingShingle |
Using location history data from cell phones of infectious patients for disease surveillance Giddaluru, Jeevan Digital epidemiology Disease surveillance Epidemiologia digital Global positioning system Malaria Malária Sistema de posicionamento global Tuberculose Tuberculosis Vigilância de doenças |
title_short |
Using location history data from cell phones of infectious patients for disease surveillance |
title_full |
Using location history data from cell phones of infectious patients for disease surveillance |
title_fullStr |
Using location history data from cell phones of infectious patients for disease surveillance |
title_full_unstemmed |
Using location history data from cell phones of infectious patients for disease surveillance |
title_sort |
Using location history data from cell phones of infectious patients for disease surveillance |
author |
Giddaluru, Jeevan |
author_facet |
Giddaluru, Jeevan |
author_role |
author |
dc.contributor.none.fl_str_mv |
Nakaya, Helder Takashi Imoto |
dc.contributor.author.fl_str_mv |
Giddaluru, Jeevan |
dc.subject.por.fl_str_mv |
Digital epidemiology Disease surveillance Epidemiologia digital Global positioning system Malaria Malária Sistema de posicionamento global Tuberculose Tuberculosis Vigilância de doenças |
topic |
Digital epidemiology Disease surveillance Epidemiologia digital Global positioning system Malaria Malária Sistema de posicionamento global Tuberculose Tuberculosis Vigilância de doenças |
description |
Infectious diseases significantly contribute to global morbidity and mortality, highlighting the critical need for robust disease surveillance systems. The rapid and accurate identification of infection hotspots is crucial for effective disease control and eliminating vector reservoirs. Traditional methods, reliant on patient-reported data, are vague, slow, and non-integrative, presenting substantial barriers to fully understanding the underlying causes of infection transmission. The widespread usage of smartphones presents a unique opportunity to access, analyze, and monitor digital data. Particularly, location data can offer potential insights into infectious disease dynamics, which has remained largely unexplored. Firstly, the present study leverages location history data from smartphones of malaria patients in Manaus, Amazonas region, to pinpoint mosquito-breeding sites. Upon quantifying the location data, the primary transmission hotspots were identified to be concentrated on the outskirts of the city of Manaus. Additionally, the quantification and hotspot validation confirmed that newly visited locations during the exposure period were potential sources of infection transmission. Secondly, the current study also employs a novel digital contact investigation method for a human-to-human transmission infection such as tuberculosis to measure the exposure risk between the active index cases and their close contacts. The digital contact investigation revealed varied exposure durations between the recruited paired index and close contact participants based on the outcome of close contact. To summarize, the present study determines distinct mobility patterns associated with both these infectious diseases, potentially aiding in drafting targeted public health strategies and policies for digital epidemiological surveillance. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-12-19 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/9/9142/tde-11032024-154311/ |
url |
https://www.teses.usp.br/teses/disponiveis/9/9142/tde-11032024-154311/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
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1815256857202130944 |