Chikungunya Beyond the Tropics : Where and When Do We Expect Disease Transmission in Europe?

Chikungunya virus disease (chikungunya) is a mosquito-borne infectious disease reported in at least 50 countries, mostly in the tropics. It has spread around the globe within the last two decades, with local outbreaks in Europe. The vector mosquito Aedes albopictus (Diptera, Culicidae) has already widely established itself in southern Europe and is spreading towards central parts of the continent. Public health authorities and policymakers need to be informed about where and when a chikungunya transmission is likely to take place. Here, we adapted a previously published global ecological niche model (ENM) by including only non-tropical chikungunya occurrence records and selecting bioclimatic variables that can reflect the temperate and sub-tropical conditions in Europe with greater accuracy. Additionally, we applied an epidemiological model to capture the temporal outbreak risk of chikungunya in six selected European cities. Overall, the non-tropical ENM captures all the previous outbreaks in Europe, whereas the global ENM had underestimated the risk. Highly suitable areas are more widespread than previously assumed. They are found in coastal areas of the Mediterranean Sea, in the western part of the Iberian Peninsula, and in Atlantic coastal areas of France. Under a worst-case scenario, even large areas of western Germany and the Benelux states are considered potential areas of transmission. For the six selected European cities, June–September (the 22th–38th week) is the most vulnerable time period, with the maximum continuous duration of a possible transmission period lasting up to 93 days (Ravenna, Italy)

Evaluating the risk for Usutu virus circulation in Europe : comparison of environmental niche models and epidemiological models

Abstract Background Usutu virus (USUV) is a mosquito-borne flavivirus, reported in many countries of Africa and Europe, with an increasing spatial distribution and host range. Recent outbreaks leading to regional declines of European common blackbird (Turdus merula) populations and a rising number of human cases emphasize the need for increased awareness and spatial risk assessment. Methods Modelling approaches in ecology and epidemiology differ substantially in their algorithms, potentially resulting in diverging model outputs. Therefore, we implemented a parallel approach incorporating two commonly applied modelling techniques: (1) Maxent, a correlation-based environmental niche model and (2) a mechanistic epidemiological susceptible-exposed-infected-removed (SEIR) model. Across Europe, surveillance data of USUV-positive birds from 2003 to 2016 was acquired to train the environmental niche model and to serve as test cases for the SEIR model. The SEIR model is mainly driven by daily mean temperature and calculates the basic reproduction number R0. The environmental niche model was run with long-term bio-climatic variables derived from the same source in order to estimate climatic suitability. Results Large areas across Europe are currently suitable for USUV transmission. Both models show patterns of high risk for USUV in parts of France, in the Pannonian Basin as well as northern Italy. The environmental niche model depicts the current situation better, but with USUV still being in an invasive stage there is a chance for under-estimation of risk. Areas where transmission occurred are mostly predicted correctly by the SEIR model, but it mostly fails to resolve the temporal dynamics of USUV events. High R0 values predicted by the SEIR model in areas without evidence for real-life transmission suggest that it may tend towards over-estimation of risk. Conclusions The results from our parallel-model approach highlight that relying on a single model for assessing vector-borne disease risk may lead to incomplete conclusions. Utilizing different modelling approaches is thus crucial for risk-assessment of under-studied emerging pathogens like USUV

Extrinsic Incubation Period of Dengue: Knowledge, Backlog, and Applications of Temperature Dependence

<p>Extrinsic Incubation Period of Dengue: Knowledge, Backlog, and Applications of Temperature Dependence</p

Overview of the available data for the temperature dependence of the EIP of dengue.

<p>Each point represents the duration until the first observed transmission or infection of SG at a given temperature in a single experiment. (A) Complete dataset, divided by study. (B) Complete dataset, divided by method used to infect the mosquitoes: results obtained by letting mosquitoes feed on infected mammals or artificial blood meals versus results obtained via intrathoracic injection of virus solution. (C) Data from mosquitoes infected via feeding, divided by the amount of virus ingested by mosquitoes. GE, genome equivalents; LD₅₀, mean lethal dose; PFU, plaque forming units. (D) Data from mosquitoes infected via feeding, divided by method of demonstration of transmission. Black circles: Transmission was demonstrated by allowing infected mosquitoes to feed on mammals. White circles: Tests on mammals yielded negative results, but SG contained virus. Grey circles: Tests on mammals were not done, but SG contained virus. Xs: Neither transmission to mammals nor SG were tested.</p