Dataset Information

East/Central/South African Genotype in a Chikungunya Outbreak, Dhaka, Bangladesh, 2017.

ABSTRACT: In 2017, an unprecedented increase in febrile illness was observed in Dhaka, Bangladesh. Real-time reverse transcription PCR confirmed that 603 (40.2%) of 1,500 cases were chikungunya fever. Phylogenetic analysis revealed circulation of the non-A226V East/Central/South African genotype of chikungunya virus in Bangladesh.

SUBMITTER: Rahman M

PROVIDER: S-EPMC6346441 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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East/Central/South African Genotype in a Chikungunya Outbreak, Dhaka, Bangladesh, 2017.

Rahman Mizanur M Yamagishi Junya J Rahim Rummana R Hasan Abu A Sobhan Abu A

Emerging infectious diseases 20190201 2

In 2017, an unprecedented increase in febrile illness was observed in Dhaka, Bangladesh. Real-time reverse transcription PCR confirmed that 603 (40.2%) of 1,500 cases were chikungunya fever. Phylogenetic analysis revealed circulation of the non-A226V East/Central/South African genotype of chikungunya virus in Bangladesh. ...[more]

PMID: 30666947

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Project description:BackgroundSeveral large outbreaks of chikungunya have been reported in the Indian Ocean region in the last decade. In 2017, an outbreak occurred in Dhaka, Bangladesh, one of the largest and densest megacities in the world. Population mobility and fluctuations in population density are important drivers of epidemics. Measuring population mobility during outbreaks is challenging but is a particularly important goal in the context of rapidly growing and highly connected cities in low- and middle-income countries, which can act to amplify and spread local epidemics nationally and internationally.MethodsWe first describe the epidemiology of the 2017 chikungunya outbreak in Dhaka and estimate incidence using a mechanistic model of chikungunya transmission parametrized with epidemiological data from a household survey. We combine the modeled dynamics of chikungunya in Dhaka, with mobility estimates derived from mobile phone data for over 4 million subscribers, to understand the role of population mobility on the spatial spread of chikungunya within and outside Dhaka during the 2017 outbreak.ResultsWe estimate a much higher incidence of chikungunya in Dhaka than suggested by official case counts. Vector abundance, local demographics, and population mobility were associated with spatial heterogeneities in incidence in Dhaka. The peak of the outbreak in Dhaka coincided with the annual Eid holidays, during which large numbers of people traveled from Dhaka to other parts of the country. We show that travel during Eid likely resulted in the spread of the infection to the rest of the country.ConclusionsOur results highlight the impact of large-scale population movements, for example during holidays, on the spread of infectious diseases. These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak analysis, forecasting, and surveillance.

Dataset Information

East/Central/South African Genotype in a Chikungunya Outbreak, Dhaka, Bangladesh, 2017.

Publications

East/Central/South African Genotype in a Chikungunya Outbreak, Dhaka, Bangladesh, 2017.

Similar Datasets

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