BackgroundVisceral leishmaniasis (VL) is a neglected tropical disease transmitted by sandflies. On the Indian subcontinent (ISC), VL is targeted for elimination as a public health problem by 2017. In the context of VL, the elimination target is defined as an annual VL incidence of <1 per 10,000 capita at (sub-)district level. Interventions focus on vector control, surveillance and on diagnosing and treating VL cases. Many endemic areas have not yet achieved optimal control due to logistical, biological as well as technical challenges. We used mathematical modelling to quantify VL transmission dynamics and predict the feasibility of achieving the VL elimination target with current control strategies under varying assumptions about the reservoir of infection in humans.MethodsWe developed three deterministic age-structured transmission models with different main reservoirs of infection in humans: asymptomatic infections (model 1), reactivation of infection after initial infection (model 2), and post kala-azar dermal leishmaniasis (PKDL; model 3). For each model, we defined four sub-variants based on different assumptions about the duration of immunity and age-patterns in exposure to sandflies. All 12 model sub-variants were fitted to data from the KalaNet study in Bihar (India) and Nepal, and the best sub-variant was selected per model. Predictions were made for optimal and sub-optimal indoor residual spraying (IRS) effectiveness for three different levels of VL endemicity.ResultsStructurally different models explained the KalaNet data equally well. However, the predicted impact of IRS varied substantially between models, such that a conclusion about reaching the VL elimination targets for the ISC heavily depends on assumptions about the main reservoir of infection in humans: asymptomatic cases, recovered (immune) individuals that reactivate, or PKDL cases.ConclusionsAvailable data on the impact of IRS so far suggest one model is probably closest to reality (model 1). According to this model, elimination of VL (incidence of <1 per 10,000) by 2017 is only feasible in low and medium endemic settings with optimal IRS. In highly endemic settings and settings with sub-optimal IRS, additional interventions will be required.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-016-1292-0) contains supplementary material, which is available to authorized users.

Between 2006 and 2009 the largest human Q fever epidemic ever described occurred in the Netherlands. The source of infection was traced back to dairy goat herds with abortion problems due to Q fever. The first aim of control measures taken in these herds was the reduction of human exposure. To analyze Q fever dynamics in goat herds and to study the effect of control measures, a within-herd model of Coxiella burnetii transmission in dairy goat herds was developed. With this individual-based stochastic model we evaluated six control strategies and three herd management styles and studied which strategy leads to a lower Q fever prevalence and/or to disease extinction in a goat herd. Parameter values were based on literature and on experimental work. The model could not be validated with independent data. The results of the epidemiological model were: (1) Vaccination is effective in quickly reducing the prevalence in a dairy goat herd. (2) When taking into account the average time to extinction of the infection and the infection pressure in a goat herd, the most effective control strategy is preventive yearly vaccination, followed by the reactive strategies to vaccinate after an abortion storm or after testing BTM (bulk tank milk) positive. (3) As C. burnetii in dried dust may affect public health, an alternative ranking method is based on the cumulative amount of C. burnetii emitted into the environment (from disease introduction until extinction). Using this criterion, the same control strategies are effective as when based on time to extinction and infection pressure (see 2). (4) As the bulk of pathogen excretion occurs during partus and abortion, culling of pregnant animals during an abortion storm leads to a fast reduction of the amount of C. burnetii emitted into the environment. However, emission is not entirely prevented and Q fever will not be eradicated in the herd by this measure. (5) A search & destroy (i.e. test and cull) method by PCR of individual milk samples with a detection probability of 50% of detecting and culling infected goats - that excrete C. burnetii intermittently - will not result in eradication of Q fever in the herd. This control strategy was the least effective of the six evaluated strategies. Subject to model limitations, our results indicate that only vaccination is capable of preventing and controlling Q fever outbreaks in dairy goat farms. Thus, preventive vaccination should be considered as an ongoing control measure.

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Even though low pathogenic avian influenza viruses (LPAIv) affect the poultry industry of several countries in the world, information about their transmission characteristics in poultry is sparse. Outbreak reports of LPAIv in layer chickens have described drops in egg production that appear to be correlated with the virus transmission dynamics. The objective of this study was to use egg production data from LPAIv infected layer flocks to quantify the within-flock transmission parameters of the virus. Egg production data from two commercial layer chicken flocks which were infected with an H7N3 LPAIv were used for this study. In addition, an isolate of the H7N3 LPAIv causing these outbreaks was used in a transmission experiment. The field and experimental estimates showed that this is a virus with high transmission characteristics. Furthermore, with the field method, the day of introduction of the virus into the flock was estimated. The method here presented uses compartmental models that assume homogeneous mixing. This method is, therefore, best suited to study transmission in commercial flocks with a litter (floor-reared) housing system. It would also perform better, when used to study transmission retrospectively, after the outbreak has finished and there is egg production data from recovered chickens. This method cannot be used when a flock was affected with a LPAIv with low transmission characteristics (R(0)<2), since the drop in egg production would be low and likely to be confounded with the expected decrease in production due to aging of the flock. Because only two flocks were used for this analysis, this study is a preliminary basis for a proof of principle that transmission parameters of LPAIv infections in layer chicken flocks could be quantified using the egg production data from affected flocks.