Publication: A spatio-temporal analysis of scrub typhus and murine typhus in laos; implications from changing landscapes and climate
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Issued Date
2021-08-01
Resource Type
ISSN
19352735
19352727
19352727
Other identifier(s)
2-s2.0-85114098830
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Mahidol University
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SCOPUS
Bibliographic Citation
PLoS Neglected Tropical Diseases. Vol.15, No.8 (2021)
Suggested Citation
Tamalee Roberts, Daniel M. Parker, Philip L. Bulterys, Sayaphet Rattanavong, Ivo Elliott, Koukeo Phommasone, Mayfong Mayxay, Vilada Chansamouth, Matthew T. Robinson, Stuart D. Blacksell, Paul N. Newton A spatio-temporal analysis of scrub typhus and murine typhus in laos; implications from changing landscapes and climate. PLoS Neglected Tropical Diseases. Vol.15, No.8 (2021). doi:10.1371/journal.pntd.0009685 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/77984
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Title
A spatio-temporal analysis of scrub typhus and murine typhus in laos; implications from changing landscapes and climate
Abstract
Background Scrub typhus (ST) and murine typhus (MT) are common but poorly understood causes of fever in Laos. We examined the spatial and temporal distribution of ST and MT, with the intent of informing interventions to prevent and control both diseases. Methodology and principle findings This study included samples submitted from 2003 to 2017 to Mahosot Hospital, Vientiane, for ST and MT investigation. Serum samples were tested using IgM rapid diagnostic tests. Patient demographic data along with meteorological and environmental data from Laos were analysed. Approximately 17% of patients were positive for either ST (1,337/8,150 patients tested) or MT (1,283/7,552 patients tested). While both diseases occurred in inhabitants from Vientiane Capital, from the univariable analysis MT was positively and ST negatively associated with residence in Vientiane Capital. ST was highly seasonal, with cases two times more likely to occur during the wet season months of July-September compared to the dry season whilst MT peaked in the dry season. Multivariable regression analysis linked ST incidence to fluctuations in relative humidity whereas MT was linked to variation in temperature. Patients with ST infection were more likely to come from villages with higher levels of surface flooding and vegetation in the 16 days leading up to diagnosis. Conclusions The data suggest that as cities expand, high risk areas for MT will also expand. With global heating and risks of attendant higher precipitation, these data suggest that the incidence and spatial distribution of both MT and ST will increase.