4,479 research outputs found

    Biased efficacy estimates in phase-III dengue vaccine trials due to heterogeneous exposure and differential detectability of primary infections across trial arms.

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    Vaccine efficacy (VE) estimates are crucial for assessing the suitability of dengue vaccine candidates for public health implementation, but efficacy trials are subject to a known bias to estimate VE toward the null if heterogeneous exposure is not accounted for in the analysis of trial data. In light of many well-characterized sources of heterogeneity in dengue virus (DENV) transmission, our goal was to estimate the potential magnitude of this bias in VE estimates for a hypothetical dengue vaccine. To ensure that we realistically modeled heterogeneous exposure, we simulated city-wide DENV transmission and vaccine trial protocols using an agent-based model calibrated with entomological and epidemiological data from long-term field studies in Iquitos, Peru. By simulating a vaccine with a true VE of 0.8 in 1,000 replicate trials each designed to attain 90% power, we found that conventional methods underestimated VE by as much as 21% due to heterogeneous exposure. Accounting for the number of exposures in the vaccine and placebo arms eliminated this bias completely, and the more realistic option of including a frailty term to model exposure as a random effect reduced this bias partially. We also discovered a distinct bias in VE estimates away from the null due to lower detectability of primary DENV infections among seronegative individuals in the vaccinated group. This difference in detectability resulted from our assumption that primary infections in vaccinees who are seronegative at baseline resemble secondary infections, which experience a shorter window of detectable viremia due to a quicker immune response. This resulted in an artefactual finding that VE estimates for the seronegative group were approximately 1% greater than for the seropositive group. Simulation models of vaccine trials that account for these factors can be used to anticipate the extent of bias in field trials and to aid in their interpretation

    The impact of the demographic transition on dengue in Thailand: Insights from a statistical analysis and mathematical modeling

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    Background: An increase in the average age of dengue hemorrhagic fever (DHF) cases has been reported in Thailand. The cause of this increase is not known. Possible explanations include a reduction in transmission due to declining mosquito populations, declining contact between human and mosquito, and changes in reporting. We propose that a demographic shift toward lower birth and death rates has reduced dengue transmission and lengthened the interval between large epidemics. Methods and Findings: Using data from each of the 72 provinces of Thailand, we looked for associations between force of infection (a measure of hazard, defined as the rate per capita at which susceptible individuals become infected) and demographic and climactic variables. We estimated the force of infection from the age distribution of cases from 1985 to 2005. We find that the force of infection has declined by 2% each year since a peak in the late 1970s and early 1980s. Contrary to recent findings suggesting that the incidence of DHF has increased in Thailand, we find a small but statistically significant decline in DHF incidence since 1985 in a majority of provinces. The strongest predictor of the change in force of infection and the mean force of infection is the median age of the population. Using mathematical simulations of dengue transmission we show that a reduced birth rate and a shift in the population's age structure can explain the shift in the age distribution of cases, reduction of the force of infection, and increase in the periodicity of multiannual oscillations of DHF incidence in the absence of other changes. Conclusions: Lower birth and death rates decrease the flow of susceptible individuals into the population and increase the longevity of immune individuals. The increase in the proportion of the population that is immune increases the likelihood that an infectious mosquito will feed on an immune individual, reducing the force of infection. Though the force of infection has decreased by half, we find that the critical vaccination fraction has not changed significantly, declining from an average of 85% to 80%. Clinical guidelines should consider the impact of continued increases in the age of dengue cases in Thailand. Countries in the region lagging behind Thailand in the demographic transition may experience the same increase as their population ages. The impact of demographic changes on the force of infection has been hypothesized for other diseases, but, to our knowledge, this is the first observation of this phenomenon

    Determination of the optimal age to vaccinate against dengue using a tetravalent dengue vaccine in Brazil

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    Dengue is endemic in most of the subtropics and tropics with half of the world's population at risk of acquiring an infection. For decades only mosquito control could aid with disease prevention. However, in December 2015 the first dengue vaccine, Dengvaxia, became available.;In this thesis a single-serotype transmission model considering the effect of vaccination is derived. Three different assumptions regarding the biting rate are made. Initially, a constant biting rate is assumed to determine the optimal vaccination age for Brazil. For a more accurate description of the dynamics, mosquito biting rate data is used later on to determine an age-dependent rate.;Lastly, instead of determining the force of infection from the biting rate, agedependent serological data is used to estimate both of these functions. The description of the human population dynamics is also improved upon by using a step-death function rather than a constant death rate.;In order to reduce the burden of dengue, the optimal vaccination age is defined to minimise the lifetime expected risk of hospitalisation or lethality. For both risk functions several theories and uncertainties surrounding the disease outcome and the effect of vaccination are studied. The impact of antibody dependent enhancement and permanent cross-immunity on the vaccination age is determined. Additionally, a vaccine-induced increase is incorporated for the risk of hospitalisation. All possible serotype combinations are considered.;The results of this work demonstrate that the optimal vaccination age depends on how the biting rate and force of infection are defined. A variety of different optimal ages for immunisation are found. These vary with the assumptions relating to serotype cross-reactions and depend particularly on whether a vaccine-induced risk is considered. Consequently, a better understanding of the disease and the effect of the vaccine is paramount for finding an accurate optimal age for dengue immunisation.Dengue is endemic in most of the subtropics and tropics with half of the world's population at risk of acquiring an infection. For decades only mosquito control could aid with disease prevention. However, in December 2015 the first dengue vaccine, Dengvaxia, became available.;In this thesis a single-serotype transmission model considering the effect of vaccination is derived. Three different assumptions regarding the biting rate are made. Initially, a constant biting rate is assumed to determine the optimal vaccination age for Brazil. For a more accurate description of the dynamics, mosquito biting rate data is used later on to determine an age-dependent rate.;Lastly, instead of determining the force of infection from the biting rate, agedependent serological data is used to estimate both of these functions. The description of the human population dynamics is also improved upon by using a step-death function rather than a constant death rate.;In order to reduce the burden of dengue, the optimal vaccination age is defined to minimise the lifetime expected risk of hospitalisation or lethality. For both risk functions several theories and uncertainties surrounding the disease outcome and the effect of vaccination are studied. The impact of antibody dependent enhancement and permanent cross-immunity on the vaccination age is determined. Additionally, a vaccine-induced increase is incorporated for the risk of hospitalisation. All possible serotype combinations are considered.;The results of this work demonstrate that the optimal vaccination age depends on how the biting rate and force of infection are defined. A variety of different optimal ages for immunisation are found. These vary with the assumptions relating to serotype cross-reactions and depend particularly on whether a vaccine-induced risk is considered. Consequently, a better understanding of the disease and the effect of the vaccine is paramount for finding an accurate optimal age for dengue immunisation
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