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- Lim, Ah-Young, et al.
(författare)
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A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk
- 2023
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Ingår i: BMC Infectious Diseases. - : BioMed Central (BMC). - 1471-2334. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.Methods: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).Results: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002–2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.Conclusions: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.
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- Ebi, Kristie L, et al.
(författare)
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Current medical research funding and frameworks are insufficient to address the health risks of global environmental change
- 2016
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Ingår i: Environmental Health. - : Springer Science and Business Media LLC. - 1476-069X. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Three major international agreements signed in 2015 are key milestones for transitioning to more sustainable and resilient societies: the UN 2030 Agenda for Sustainable Development; the Sendai Framework for Disaster Risk Reduction; and the Paris Agreement under the United Nations Framework Convention on Climate Change. Together, these agreements underscore the critical importance of understanding and managing the health risks of global changes, to ensure continued population health improvements in the face of significant social and environmental change over this century.Body: Funding priorities of major health institutions and organizations in the U.S. and Europe do not match research investments with needs to inform implementation of these international agreements. In the U.S., the National Institutes of Health commit 0.025 % of their annual research budget to climate change and health. The European Union Seventh Framework Programme committed 0.08 % of the total budget to climate change and health; the amount committed under Horizon 2020 was 0.04 % of the budget. Two issues apparently contributing to this mismatch are viewing climate change primarily as an environmental problem, and therefore the responsibility of other research streams; and narrowly framing research into managing the health risks of climate variability and change from the perspective of medicine and traditional public health. This reductionist, top-down perspective focuses on proximate, individual level risk factors. While highly successful in reducing disease burdens, this framing is insufficient to protect health and well-being over a century that will be characterized by profound social and environmental changes.Conclusions: International commitments in 2015 underscored the significant challenges societies will face this century from climate change and other global changes. However, the low priority placed on understanding and managing the associated health risks by national and international research institutions and organizations leaves populations poorly prepared to cope with changing health burdens. Risk-centered, systems approaches can facilitate understanding of the complex interactions and dependencies across environmental, social, and human systems. This understanding is needed to formulate effective interventions targeting socio-environmental factors that are as important for determining health burdens as are individual risk factors.
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- Farooq, Zia, et al.
(författare)
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Artificial intelligence to predict West Nile virus outbreaks with eco-climatic drivers
- 2022
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Ingår i: The Lancet Regional Health - Europe. - : Elsevier BV. - 2666-7762. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: In Europe, the frequency, intensity, and geographic range of West Nile virus (WNV)-outbreaks have increased over the past decade, with a 7.2-fold increase in 2018 compared to 2017, and a markedly expanded geographic area compared to 2010. The reasons for this increase and range expansion remain largely unknown due to the complexity of the transmission pathways and underlying disease drivers. In a first, we use advanced artificial intelligence to disentangle the contribution of eco-climatic drivers to WNV-outbreaks across Europe using decade-long (2010-2019) data at high spatial resolution. Methods: We use a high-performance machine learning classifier, XGBoost (eXtreme gradient boosting) combined with state-of-the-art XAI (eXplainable artificial intelligence) methodology to describe the predictive ability and contribution of different drivers of the emergence and transmission of WNV-outbreaks in Europe, respectively. Findings: Our model, trained on 2010-2017 data achieved an AUC (area under the receiver operating characteristic curve) score of 0.97 and 0.93 when tested with 2018 and 2019 data, respectively, showing a high discriminatory power to classify a WNV-endemic area. Overall, positive summer/spring temperatures anomalies, lower water availability index (NDWI), and drier winter conditions were found to be the main determinants of WNV-outbreaks across Europe. The climate trends of the preceding year in combination with eco-climatic predictors of the first half of the year provided a robust predictive ability of the entire transmission season ahead of time. For the extraordinary 2018 outbreak year, relatively higher spring temperatures and the abundance of Culex mosquitoes were the strongest predictors, in addition to past climatic trends. Interpretation: Our AI-based framework can be deployed to trigger rapid and timely alerts for active surveillance and vector control measures in order to intercept an imminent WNV-outbreak in Europe. Funding: The work was partially funded by the Swedish Research Council FORMAS for the project ARBOPREVENT (grant agreement 2018-05973).
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- Farooq, Zia, et al.
(författare)
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European projections of West Nile virus transmission under climate change scenarios
- 2023
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Ingår i: One Health. - : Elsevier. - 2352-7714. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- West Nile virus (WNV), a mosquito-borne zoonosis, has emerged as a disease of public health concern in Europe. Recent outbreaks have been attributed to suitable climatic conditions for its vectors favoring transmission. However, to date, projections of the risk for WNV expansion under climate change scenarios is lacking. Here, we estimate the WNV-outbreaks risk for a set of climate change and socioeconomic scenarios. We delineate the potential risk-areas and estimate the growth in the population at risk (PAR). We used supervised machine learning classifier, XGBoost, to estimate the WNV-outbreak risk using an ensemble climate model and multi-scenario approach. The model was trained by collating climatic, socioeconomic, and reported WNV-infections data (2010−22) and the out-of-sample results (1950–2009, 2023–99) were validated using a novel Confidence-Based Performance Estimation (CBPE) method. Projections of area specific outbreak risk trends, and corresponding population at risk were estimated and compared across scenarios. Our results show up to 5-fold increase in West Nile virus (WNV) risk for 2040-60 in Europe, depending on geographical region and climate scenario, compared to 2000-20. The proportion of disease-reported European land areas could increase from 15% to 23-30%, putting 161 to 244 million people at risk. Across scenarios, Western Europe appears to be facing the largest increase in the outbreak risk of WNV. The increase in the risk is not linear but undergoes periods of sharp changes governed by climatic thresholds associated with ideal conditions for WNV vectors. The increased risk will require a targeted public health response to manage the expansion of WNV with climate change in Europe.
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- Liu, Ying, et al.
(författare)
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Reviewing estimates of the basic reproduction number for dengue, Zika and chikungunya across global climate zones
- 2020
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Ingår i: Environmental Research. - : Elsevier. - 0013-9351 .- 1096-0953. ; 182
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Globally, dengue, Zika virus, and chikungunya are important viral mosquito-borne diseases that infect millions of people annually. Their geographic range includes not only tropical areas but also sub-tropical and temperate zones such as Japan and Italy. The relative severity of these arboviral disease outbreaks can vary depending on the setting. In this study we explore variation in the epidemiologic potential of outbreaks amongst these climatic zones and arboviruses in order to elucidate potential reasons behind such differences.METHODOLOGY: We reviewed the peer-reviewed literature (PubMed) to obtain basic reproduction number (R0) estimates for dengue, Zika virus, and chikungunya from tropical, sub-tropical and temperate regions. We also computed R0 estimates for temperate and sub-tropical climate zones, based on the outbreak curves in the initial outbreak phase. Lastly we compared these estimates across climate zones, defined by latitude.RESULTS: Of 2115 studies, we reviewed the full text of 128 studies and included 65 studies in our analysis. Our results suggest that the R0 of an arboviral outbreak depends on climate zone, with lower R0 estimates, on average, in temperate zones (R0 = 2.03) compared to tropical (R0 = 3.44) and sub-tropical zones (R0 = 10.29). The variation in R0 was considerable, ranging from 0.16 to 65. The largest R0 was for dengue (65) and was estimated by the Ross-Macdonald model in the tropical zone, whereas the smallest R0 (0.16) was for Zika virus and was estimated statistically from an outbreak curve in the sub-tropical zone.CONCLUSIONS: The results indicate climate zone to be an important determinant of the basic reproduction number, R0, for dengue, Zika virus, and chikungunya. The role of other factors as determinants of R0, such as methods, environmental and social conditions, and disease control, should be further investigated. The results suggest that R0 may increase in temperate regions in response to global warming, and highlight the increasing need for strengthening preparedness and control activities.
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