Inapparent infections shape the transmission heterogeneity of dengue

Abstract

Transmission heterogeneity, whereby a disproportionate fraction of pathogen transmission events result from a small number of individuals or geographic locations, is an inherent property of many, if not most, infectious disease systems. For vector-borne diseases, transmission heterogeneity is inferred from the distribution of the number of vectors per host, which could lead to significant bias in situations where vector abundance and transmission risk at the household do not correlate, as is the case with dengue virus (DENV). We used data from a contact tracing study to quantify the distribution of DENV acute infections within human activity spaces (AS), the collection of residential locations an individual routinely visits, and quantified measures of virus transmission heterogeneity from two consecutive dengue outbreaks (DENV-4 and DENV-2) that occurred in the city of Iquitos, Peru. Negative-binomial distributions and Pareto fractions showed evidence of strong overdispersion in the number of DENV infections by AS and identified super-spreading units (SSUs): i.e. AS where most infections occurred. Approximately 8% of AS were identified as SSUs, contributing to more than 50% of DENV infections. SSU occurrence was associated more with DENV-2 infection than with DENV-4, a predominance of inapparent infections (74% of all infections), households with high Aedes aegypti mosquito abundance, and high host susceptibility to the circulating DENV serotype. Marked heterogeneity in dengue case distribution, and the role of inapparent infections in defining it, highlight major challenges faced by reactive interventions if those transmission units contributing the most to transmission are not identified, prioritized, and effectively treated.

Keywords: arbovirus; mobility; super-spreading; transmission heterogeneity.

Fig. 1.

Quantifying DENV transmission heterogeneity. (a) The contact-cluster study design incorporated data from active surveillance in Iquitos, Peru, with two entomological surveys to quantify the offspring distribution of DENV infections. (b) Temporal distribution of the 253 index cases and their associated secondary cases by serotype.

Fig. 2.

Heterogeneities in DENV transmission. The number of acute infections per activity space, Z_AS, was estimated for 257 index cases detected in Iquitos from 2008 to 2014. Histograms in (a) and (b) show Z_AS values across all clusters for DENV-2 and DENV-4, respectively. (c) Estimates of k, the dispersion parameter for a negative-binomial distribution, for each virus and the time of detection of an acute DENV infection (Dt) in a different person in the same activity space. (d) Estimates of k as a function of Dt for symptomatic and inapparent infections. All data points, with the exception of those with * had their parameter k being higher than unity (Table S2).

Fig. 3.

Fraction of AS units contributing with most DENV cases. (a–c) Plots showing the estimation of the Pareto fractions of Z_AS (shown as cumulative fraction, blue) representing the %th fraction of cases occurring in the %th fraction of AS units. The Pareto fraction is shown in ratio format (##:##). Gray lines show 50:50 Pareto fraction. Fits were performed for (a) symptomatic infections, (b) all infections (symptomatic and inapparent) and (c) the number of Ae. aegypti per AS. Panel (d) shows the number of Ae. Aegypti and Z_AS.

Fig. 4.

Factors influencing the emergence of DENV SSUs. GAMM-predicted association between the probability of an activity space being a DENV super-spreading unit, the total number of Ae. aegypti mosquitoes sampled in the AS, and the proportion of individuals in the AS susceptible to the circulating serotype (Si).