Estimating Dengue Transmission Intensity from Sero-Prevalence Surveys in Multiple Countries
Author(s) -
Natsuko Imai,
Ilaria Dorigatti,
Simon Cauchemez,
Neil M. Ferguson
Publication year - 2015
Publication title -
plos neglected tropical diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.99
H-Index - 135
eISSN - 1935-2735
pISSN - 1935-2727
DOI - 10.1371/journal.pntd.0003719
Subject(s) - dengue fever , transmission (telecommunications) , dengue vaccine , seroprevalence , serotype , medicine , basic reproduction number , subclinical infection , immunology , dengue virus , demography , virology , environmental health , population , antibody , serology , sociology , electrical engineering , engineering
Background Estimates of dengue transmission intensity remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing both the burden of disease from dengue and the likely impact of interventions. Methodology/Principal Findings The force of infection ( λ ) and corresponding basic reproduction numbers ( R 0 ) for dengue were estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalence surveys identified from the literature. The majority of R 0 estimates ranged from 1–4. Assuming that two heterologous infections result in complete immunity produced up to two-fold higher estimates of R 0 than when tertiary and quaternary infections were included. λ estimated from IgG data were comparable to the sum of serotype-specific forces of infection derived from PRNT data, particularly when inter-serotype interactions were allowed for. Conclusions/Significance Our analysis highlights the highly heterogeneous nature of dengue transmission. How underlying assumptions about serotype interactions and immunity affect the relationship between the force of infection and R 0 will have implications for control planning. While PRNT data provides the maximum information, our study shows that even the much cheaper ELISA-based assays would provide comparable baseline estimates of overall transmission intensity which will be an important consideration in resource-constrained settings.
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