6 research outputs found

    Current and future distribution of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in WHO Eastern Mediterranean Region

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    Abstract Background Aedes-borne diseases as dengue, zika, chikungunya and yellow fever are an emerging problem worldwide, being transmitted by Aedes aegypti and Aedes albopictus. Lack of up to date information about the distribution of Aedes species hampers surveillance and control. Global databases have been compiled but these did not capture data in the WHO Eastern Mediterranean Region (EMR), and any models built using these datasets fail to identify highly suitable areas where one or both species may occur. The first objective of this study was therefore to update the existing Ae. aegypti (Linnaeus, 1762) and Ae. albopictus (Skuse, 1895) compendia and the second objective was to generate species distribution models targeted to the EMR. A final objective was to engage the WHO points of contacts within the region to provide feedback and hence validate all model outputs. Methods The Ae. aegypti and Ae. albopictus compendia provided by Kraemer et al. (Sci Data 2:150035, 2015; Dryad Digit Repos, 2015) were used as starting points. These datasets were extended with more recent species and disease data. In the next step, these sets were filtered using the Köppen–Geiger classification and the Mahalanobis distance. The occurrence data were supplemented with pseudo-absence data as input to Random Forests. The resulting suitability and maximum risk of establishment maps were combined into hard-classified maps per country for expert validation. Results The EMR datasets consisted of 1995 presence locations for Ae. aegypti and 2868 presence locations for Ae. albopictus. The resulting suitability maps indicated that there exist areas with high suitability and/or maximum risk of establishment for these disease vectors in contrast with previous model output. Precipitation and host availability, expressed as population density and night-time lights, were the most important variables for Ae. aegypti. Host availability was the most important predictor in case of Ae. albopictus. Internal validation was assessed geographically. External validation showed high agreement between the predicted maps and the experts’ extensive knowledge of the terrain. Conclusion Maps of distribution and maximum risk of establishment were created for Ae. aegypti and Ae. albopictus for the WHO EMR. These region-specific maps highlighted data gaps and these gaps will be filled using targeted monitoring and surveillance. This will increase the awareness and preparedness of the different countries for Aedes borne diseases

    Public health impact of the spread of Anopheles stephensi in the WHO Eastern Mediterranean Region countries in Horn of Africa and Yemen: need for integrated vector surveillance and control

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    Abstract Background Anopheles stephensi is an efficient vector of both Plasmodium falciparum and Plasmodium vivax in South Asia and the Middle East. The spread of An. stephensi to countries within the Horn of Africa threatens progress in malaria control in this region as well as the rest of sub-Saharan Africa. Methods The available malaria data and the timeline for the detection of An. stephensi was reviewed to analyse the role of An. stephensi in malaria transmission in Horn of Africa of the Eastern Mediterranean Region (EMR) in Djibouti, Somalia, Sudan and Yemen. Results Malaria incidence in Horn of Africa of EMR and Yemen, increased from 41.6 in 2015 to 61.5 cases per 1000 in 2020. The four countries from this region, Djibouti, Somalia, Sudan and Yemen had reported the detection of An. stephensi as of 2021. In Djibouti City, following its detection in 2012, the estimated incidence increased from 2.5 cases per 1000 in 2013 to 97.6 cases per 1000 in 2020. However, its contribution to malaria transmission in other major cities and in other countries, is unclear because of other factors, quality of the urban malaria data, human mobility, uncertainty about the actual arrival time of An. stephensi and poor entomological surveillance. Conclusions While An. stephensi may explain a resurgence of malaria in Djibouti, further investigations are needed to understand its interpretation trends in urban malaria across the greater region. More investment for multisectoral approach and integrated surveillance and control should target all vectors particularly malaria and dengue vectors to guide interventions in urban areas

    SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

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    Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
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