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Int J Infect Dis ; 97: 306-312, 2020 Aug.
Article in English | MEDLINE | ID: mdl-32497797

ABSTRACT

BACKGROUND: Outbreak investigations typically focus their efforts on identifying cases that present at healthcare facilities. However, these cases rarely represent all cases in the wider community. In this context, community-based investigations may provide additional insight into key risk factors for infection, however, the benefits of these more laborious data collection strategies remains unclear. METHODS: We used different subsets of the data from a comprehensive outbreak investigation to compare the inferences we make in alternative investigation strategies. RESULTS: The outbreak investigation team interviewed 1,933 individuals from 460 homes. 364 (18%) of individuals had symptoms consistent with chikungunya. A theoretical clinic-based study would have identified 26% of the cases. Adding in community-based cases provided an overall estimate of the attack rate in the community. Comparison with controls from the same household revealed that those with at least secondary education had a reduced risk. Finally, enrolling residents from households across the community allowed us to characterize spatial heterogeneity of risk and identify the type of clothing usually worn and travel history as risk factors. This also revealed that household-level use of mosquito control was not associated with infection. CONCLUSIONS: These findings highlight that while clinic-based studies may be easier to conduct, they only provide limited insight into the burden and risk factors for disease. Enrolling people who escaped from infection, both in the household and in the community allows a step change in our understanding of the spread of a pathogen and maximizes opportunities for control.


Subject(s)
Chikungunya Fever/epidemiology , Adolescent , Adult , Aged , Animals , Bangladesh/epidemiology , Child , Child, Preschool , Disease Outbreaks , Family Characteristics , Female , Humans , Incidence , Male , Middle Aged , Residence Characteristics/statistics & numerical data , Risk Factors , Young Adult
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