Infection with influenza A(H1N1)pdm09 during the first wave of the 2009 pandemic: Evidence from a longitudinal seroepidemiologic study in Dhaka, Bangladesh. Issue 5 (26th July 2017) - Nasreen, Sharifa; Rahman, Mustafizur; Hancock, Kathy; Katz, Jacqueline M.; Goswami, Doli; Sturm‐Ramirez, Katharine; Holiday, Crystal; Jefferson, Stacie; Branch, Alicia; Wang, David; Veguilla, Vic; Widdowson, Marc‐Alain; et al.
Abstract : Background: We determined influenza A(H1N1)pdm09 antibody levels before and after the first wave of the pandemic in an urban community in Dhaka, Bangladesh. Methods: We identified a cohort of households by stratified random sampling. We collected baseline serum specimens during July‐August 2009, just prior to the initial wave of the 2009 pandemic in this community and a second specimen during November 2009, after the pandemic peak. Paired sera were tested for antibodies against A(H1N1)pdm09 virus using microneutralization assay and hemagglutinin inhibition (HI) assay. A fourfold increase in antibody titer by either assay with a titer of ≥40 in the convalescent sera was considered a seroconversion. At baseline, an HI titer of ≥40 was considered seropositive. We collected information on clinical illness from weekly home visits. Results: We tested 779 paired sera from the participants. At baseline, before the pandemic wave, 1% overall and 3% of persons >60 years old were seropositive. After the first wave of the pandemic, 211 (27%) individuals seroconverted against A(H1N1)pdm09. Children aged 5‐17 years had the highest proportion (37%) of seroconversion. Among 264 (34%) persons with information on clinical illness, 191 (72%) had illness >3 weeks prior to collection of the follow‐up sera and 73 (38%) seroconverted. Sixteen (22%) of these 73 seroconverted participants reported no clinical illness. Conclusion: After the first pandemic wave in Dhaka, one in four persons were infected by A(H1N1)pdm09 virus and the highest burden of infection was among the school‐aged children. Seroprevalence studies supplement traditional surveillance systems to estimate infection burden.