Relationship between Transmission Intensity and Incidence of Dengue Hemorrhagic Fever in Thailand

Abstract

BackgroundDengue is the most prevalent mosquito-borne virus, and potentially fatal dengue hemorrhagic fever (DHF) occurs mainly in secondary infections. It recently was hypothesized that, due to the presence of cross-immunity, the relationship between the incidence of DHF and transmission intensity may be negative at areas of intense transmission. We tested this hypothesis empirically, using vector abundance as a surrogate of transmission intensity.Methodology/Principal FindingsHouse Index (HI), which is defined as the percentage of households infested with vector larvae/pupae, was obtained from surveys conducted on one million houses in Thailand, between 2002 and 2004. First, the utility of HI as a surrogate of transmission intensity was confirmed because HI was correlated negatively with mean age of DHF in the population. Next, the relationship between DHF incidence and HI was investigated. DHF incidence increased only up to an HI of about 30, but declined thereafter. Reduction of HI from the currently maximal level to 30 would increase the incidence by more than 40%. Simulations, which implemented a recently proposed model for cross-immunity, generated results that resembled actual epidemiological data. It was predicted that cross-immunity generates a wide variation in incidence, thereby obscuring the relationship between incidence and transmission intensity. The relationship would become obvious only if data collected over a long duration (e.g., >10 years) was averaged.ConclusionThe negative relationship between DHF incidence and dengue transmission intensity implies that in regions of intense transmission, insufficient reduction of vector abundance may increase long-term DHF incidence. Further studies of a duration much longer than the present study, are warranted.

Spatial Evaluation and Modeling of Dengue Seroprevalence and Vector Density in Rio de Janeiro, Brazil

“…We hypothesize that such isolated populations are too small to maintain the dengue virus endemically and that the observed seroprevalence maps are the result of multiple viral introductions through the last 20 years, always through the same entrance. Such spatial clustering of dengue has being reported in the literature [45],[46], and supports the hypothesis that mosquito-borne disease incidence is highly focal [46],[62]. On the other hand, a spatial pattern was not observed in Higienópolis, a neighborhood with multiple accesses and surrounded by slums with high population density.…”

Control of Aedes aegypti Breeding: A Novel Intervention for Prevention and Control of Dengue in an Endemic Zone of Delhi, India

“…HI, BI, CI and PI and dengue transmission/ dengue outbreak prediction[19], [20],whereas other reported that either of these indices or their combination has importance in prediction of the risk of dengue transmission/dengue outbreak[21–23]. It has been suggested that Container Pupal Index and proportion of containers positive with pupae be taken the basis for vector surveillance and disease control [24].…”

Outcome of the public consultation on the draft Scientific Opinion of the Scientific Panel on Genetically Modified Organisms providing guidance on the environmental risk assessment of genetically modified animals

“…Further, long-term suppression may fail due to effects discussed above such as loss of fitness or development of resistance. Cross-immunity as well as immunity may be important: for example, Oxitec's models of dengue transmission (Yakob et al, 2008;Alphey et al, 2011b) omit the important effects of cross-immunity between multiple serotypes of dengue fever on the incidence of dengue haemorrhagic fever and thus assume that only beneficial impacts on disease impacts can occur, when in practice there could be significant harm if population suppression in high-transmission areas is only partially effective (Thammapalo et al, 2008;Nagao & Koelle, 2008;GeneWatch UK, 2012). The most serious and often fatal form of dengue, dengue hemorrhagic fever (DHF), appears to be more likely when a person is infected by a second serotype of dengue fever, having already been infected by one of the other serotypes.…”

“…For disease prevention, the ultimate endpoint is disease incidence and severity : it is important that this is assessed because successful population suppression does not necessarily mean less, or less severe, disease , due to issues such as disease transmission thresholds and human immunity and cross-immunity (see comments on Section 4.2.6). Again, multiple conceptual models need to be considered to identify worst-case scenarios: for example, Oxitec's models of dengue transmission (Yakob et al, 2008;Alphey et al, 2011b) omit the important effects of cross-immunity on the incidence of dengue haemorrhagic fever and thus assume that only beneficial impacts on disease impacts can occur, when in practice there could be significant harm if population suppression in high-transmission areas is only partially effective (Thammapalo et al, 2008;Nagao & Koelle, 2008;GeneWatch UK, 2012). If the right concepts and mechanisms are not in the model in the first place, potentially serious risks may not be identified.…”

“…For example, releases of GM mosquitoes in a population suppression approach may be only partially or temporarily effective at suppressing populations. In the case of dengue vectors, a partial reduction in mosquito numbers in dengueendemic areas can lead to an increase in cases of dengue hemorrhagic fever (the more severe and often fatal form of the disease) (Thammapalo et al, 2008;Nagao & Koelle, 2008). Such potential negative impacts on human health are not captured in a methodology which focuses on exposure to the GM organism: they are not caused by exposure to the GM organism but by the complex interactions between the release programme for the GMO, ecosystems, humans and disease.…”