Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
1.
J Infect Dis ; 223(3): 399-402, 2021 02 13.
Artigo em Inglês | MEDLINE | ID: mdl-33000172

RESUMO

Social distancing (SD) measures aimed at curbing the spread of SARS-CoV-2 remain an important public health intervention. Little is known about the collateral impact of reduced mobility on the risk of other communicable diseases. We used differences in dengue case counts pre- and post implementation of SD measures and exploited heterogeneity in SD treatment effects among different age groups in Singapore to identify the spillover effects of SD measures. SD policy caused an increase of over 37.2% in dengue cases from baseline. Additional measures to preemptively mitigate the risk of other communicable diseases must be considered before the implementation/reimplementation of SARS-CoV-2 SD measures.


Assuntos
COVID-19/transmissão , Dengue/transmissão , Distanciamento Físico , Adolescente , Adulto , Idoso , COVID-19/epidemiologia , COVID-19/virologia , Criança , Pré-Escolar , Dengue/epidemiologia , Dengue/virologia , Humanos , Pessoa de Meia-Idade , Saúde Pública , Fatores de Risco , SARS-CoV-2/isolamento & purificação , Singapura/epidemiologia , Adulto Jovem
2.
Proc Biol Sci ; 287(1933): 20201173, 2020 08 26.
Artigo em Inglês | MEDLINE | ID: mdl-32842911

RESUMO

SARS-CoV-2 is a new pathogen responsible for the coronavirus disease 2019 (COVID-19) outbreak. Southeast Asia was the first region to be affected outside China, and although COVID-19 cases have been reported in all countries of Southeast Asia, both the policies and epidemic trajectories differ substantially, potentially due to marked differences in social distancing measures that have been implemented by governments in the region. This paper studies the across-country relationships between social distancing and each population's response to policy, the subsequent effects of these responses to the transmissibility and epidemic trajectories of SARS-CoV-2. The analysis couples COVID-19 case counts with real-time mobility data across Southeast Asia to estimate the effects of host population response to social distancing policy and the subsequent effects on the transmissibility and epidemic trajectories of SARS-CoV-2. A novel inference strategy for the time-varying reproduction number is developed to allow explicit inference of the effects of social distancing on the transmissibility of SARS-CoV-2 through a regression structure. This framework replicates the observed epidemic trajectories across most Southeast Asian countries, provides estimates of the effects of social distancing on the transmissibility of disease and can simulate epidemic histories conditional on changes in the degree of intervention scenarios and compliance within Southeast Asia.


Assuntos
Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Quarentena/métodos , Sudeste Asiático/epidemiologia , Betacoronavirus , COVID-19 , Infecções por Coronavirus/epidemiologia , Política de Saúde , Humanos , Pneumonia Viral/epidemiologia , Quarentena/legislação & jurisprudência , SARS-CoV-2
3.
BMC Infect Dis ; 20(1): 927, 2020 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-33276742

RESUMO

BACKGROUND: Thailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied. METHODS: We develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level. RESULTS: Two dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools. CONCLUSIONS: Importation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand.


Assuntos
Vírus da Dengue/genética , Dengue/epidemiologia , Dengue/transmissão , Epidemias , Modelos Estatísticos , Teorema de Bayes , Clima , Análise por Conglomerados , Dengue/virologia , Doenças Endêmicas , Alocação de Recursos para a Atenção à Saúde , Humanos , Sorogrupo , Tailândia/epidemiologia , População Urbana , Urbanização
4.
PLoS Negl Trop Dis ; 14(10): e0008719, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33119609

RESUMO

An estimated 105 million dengue infections occur per year across 120 countries, where traditional vector control is the primary control strategy to reduce contact between mosquito vectors and people. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. Here we examine the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst adjusting for temporal confounders. We found that social distancing is expected to lead to 4.32 additional cases per 100,000 individuals in Thailand per month, which equates to 170 more cases per month in the Bangkok province (95% CI: 100-242) and 2008 cases in the country as a whole (95% CI: 1170-2846). Social distancing policy estimates for Thailand were also found to be robust to model misspecification, and variable addition and omission. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies.


Assuntos
Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/epidemiologia , Dengue/transmissão , Pneumonia Viral/epidemiologia , Animais , Betacoronavirus , COVID-19 , Infecções por Coronavirus/prevenção & controle , Dengue/epidemiologia , Humanos , Malásia/epidemiologia , Mosquitos Vetores , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , SARS-CoV-2 , Singapura/epidemiologia , Isolamento Social , Tailândia/epidemiologia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA