Dataset Information

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh.

ABSTRACT:

Background

Several 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.

Methods

We 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.

Results

We 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.

Conclusions

Our 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.

SUBMITTER: Mahmud AS

PROVIDER: S-EPMC7880496 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh.

Mahmud Ayesha S AS Kabir Md Iqbal MI Engø-Monsen Kenth K Tahmina Sania S Riaz Baizid Khoorshid BK Hossain Md Akram MA Khanom Fahmida F Rahman Md Mujibor MM Rahman Md Khalilur MK Sharmin Mehruba M Hossain Dewan Mashrur DM Yasmin Shakila S Ahmed Md Mokhtar MM Lusha Mirza Afreen Fatima MAF Buckee Caroline O CO

PLoS neglected tropical diseases 20210202 2

<h4>Background</h4>Several 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 ...[more]

PMID: 33529229

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Project description:BackgroundThe first identified Chikungunya outbreak occurred in Bangladesh in 2008. In late October 2011, a local health official from Dohar Sub-district, Dhaka District, reported an outbreak of undiagnosed fever and joint pain. We investigated the outbreak to confirm the etiology, describe the clinical presentation, and identify associated vectors.MethodologyDuring November 2-21, 2011, we conducted house-to-house surveys to identify suspected cases, defined as any inhabitant of Char Kushai village with fever followed by joint pain in the extremities with onset since August 15, 2011. We collected blood specimens and clinical histories from self-selected suspected cases using a structured questionnaire. Blood samples were tested for IgM antibodies against Chikungunya virus. The village was divided into nine segments and we collected mosquito larvae from water containers in seven randomly selected houses in each segment. We calculated the Breteau index for the village and identified the mosquito species.ResultsThe attack rate was 29% (1105/3840) and 29% of households surveyed had at least one suspected case: 15% had ≥3. The attack rate was 38% (606/1589) in adult women and 25% in adult men (320/1287). Among the 1105 suspected case-patients, 245 self-selected for testing and 80% of those (196/245) had IgM antibodies. In addition to fever and joint pain, 76% (148/196) of confirmed cases had rash and 38%(75/196) had long-lasting joint pain. The village Breteau index was 35 per 100 and 89%(449/504) of hatched mosquitoes were Aedes albopictus.ConclusionThe evidence suggests that this outbreak was due to Chikungunya. The high attack rate suggests that the infection was new to this area, and the increased risk among adult women suggests that risk of transmission may have been higher around households. Chikungunya is an emerging infection in Bangladesh and current surveillance and prevention strategies are insufficient to mount an effective public health response.

Project description:Chikungunya virus causes mosquito-transmitted infection that leads to extensive morbidity affecting substantial quality of life. Disease associated morbidity, quality of life, and financial loss are seldom reported in resources limited countries, such as Bangladesh. We reported the acute clinical profile, quality of life and consequent economic burden of the affected individuals in the recent chikungunya outbreak (May to September 2017) in Dhaka city, Bangladesh.We conducted a cross-sectional study during the peak of chikungunya outbreak (July 24 to August 5, 2017) to document the clinical profiles of confirmed cases (laboratory test positive) and probable cases diagnosed by medical practitioners. Data related to clinical symptoms, treatment cost, loss of productivity due to missing work days, and quality of life during their first two-weeks of symptom onset were collected via face to face interview using a structured questionnaire. World Health Organization endorsed questionnaire was used to assess the quality of life.A total of 1,326 chikungunya cases were investigated. Multivariate analysis of major clinical variables showed no statistically significant differences between confirmed and probable cases. All the patients reported joint pain and fever. Other more frequently reported symptoms include headache, loss of appetite, rash, myalgia, and itching. Arthralgia was polyarticular in 56.3% of the patients. Notably, more than 70% patients reported joint pain as the first presenting symptom. About 83% of the patients reported low to very low overall quality of life. Nearly 30% of the patients lost more than 10 days of productivity due to severe arthropathy.This study represents one of the largest samples studied so far around the world describing the clinical profile of chikungunya infection. Our findings would contribute to establish an effective syndromic surveillance system for early detection and timely public health intervention of future chikungunya outbreaks in resource-limited settings like Bangladesh.

Project description:BACKGROUND:Household contacts of cholera patients have a 100 times higher risk of developing a cholera infection than the general population. To compare the genetic relatedness of clinical and water source Vibrio cholerae isolates from cholera patients' households across three outbreaks, we analyzed these isolates using whole-genome-sequencing (WGS) and multilocus variable-number tandem-repeat analysis (MLVA). RESULTS:The WGS analyses revealed that 80% of households had source water isolates that were more closely related to clinical isolates from the same household than to any other isolates. While in another 20% of households an isolate from a person was more closely related to clinical isolates from another household than to source water isolates from their own household. The mean pairwise differences in single nucleotide-variant (SNV) counts for isolates from the same household were significantly lower than those for different households (2.4 vs. 7.7 p < 0.0001), and isolates from the same outbreak had significantly fewer mean pairwise differences compared to isolates from different outbreaks (mean: 6.2 vs. 8.0, p < 0.0001). Based on MLVA in outbreak 1, we observed that the majority of households had clinical isolates with MLVA genotypes related to other clinical isolates and unrelated to water source isolates from the same household. While in outbreak 3, there were different MLVA genotypes between households, however within the majority of households, the clinical and water source isolates had the same MLVA genotypes. The beginning of outbreak 2 resembled outbreak 1 and the latter part resembled outbreak 3. We validated our use of MLVA by comparing it to WGS. Isolates with the identical MLVA genotype had significantly fewer mean pairwise SNV differences than those isolates with different MLVA genotypes (mean: 4.8 vs. 7.7, p < 0.0001). Furthermore, consistent with WGS results, the number of pairwise differences in the five MLVA loci for isolates within the same household was significantly lower than isolates from different households (mean: 1.6 vs. 3.0, p < 0.0001). CONCLUSION:These results suggest that transmission patterns for cholera are a combination of person-to-person and water-to-person cholera transmission with the proportions of the two modes varying within and between outbreaks.

Dataset Information

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh.

Background

Methods

Results

Conclusions

Publications

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh.

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