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Climate Change and Vector-Borne Diseases: A Scoping Review on the Ecological and Public Health Impacts

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Abstract

Climate change is increasingly recognized as a significant driver of ecological and public health changes, particularly concerning vectorborne diseases. This scoping review aims to systematically map the current research on the impact of climate change on vector ecology and the subsequent effects on disease transmission dynamics. We conducted a comprehensive literature review across multiple databases to identify critical vectors, such as mosquitoes, ticks, and fleas. We examined how climate variables like temperature, precipitation, and humidity affect their populations, behaviors, and life cycles. Additionally, we explored the shifting geographic distributions of these vectors, investigating how climate change influences their spread and the emergence of diseases such as malaria, dengue, and Lyme disease in new regions. The review highlights the complex and multifaceted interactions between climate change and vector-borne diseases, emphasizing the necessity of understanding these relationships to inform effective public health strategies. Our findings indicate considerable variability in the impacts of climate change across different regions and vector species, underscoring the need for localized studies and tailored interventions. Moreover, significant research gaps were identified, particularly in predictive modeling, long-term surveillance, and the socio-economic impacts of vector-borne diseases exacerbated by climate change. We suggest directions for future research, including the development of integrated climate-health models and enhanced disease surveillance systems, to better anticipate and mitigate the effects of climate change on vector-borne disease transmission. This review underscores the urgency of addressing climate change as a critical component of global health initiatives and the importance of interdisciplinary approaches in tackling this complex issue.

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Vector‐borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito‐borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito‐borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector‐borne pathogen transmission.
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The geographic range of the blacklegged tick, Ixodes scapularis, is expanding northward from the United States into southern Canada, and studies suggest that the lone star tick, Amblyomma americanum, will follow suit. These tick species are vectors for many zoonotic pathogens, and their northward range expansion presents a serious threat to public health. Climate change (particularly increasing temperature) has been identified as an important driver permitting northward range expansion of blacklegged ticks, but the impacts of host movement, which is essential to tick dispersal into new climatically suitable regions, have received limited investigation. Here, a mechanistic movement model was applied to landscapes of eastern North America to explore 1) relationships between multiple ecological drivers and the speed of the northward invasion of blacklegged ticks infected with the causative agent of Lyme disease, Borrelia burgdorferi sensu stricto, and 2) its capacity to simulate the northward range expansion of infected blacklegged ticks and uninfected lone star ticks under theoretical scenarios of increasing temperature. Our results suggest that the attraction of migratory birds (long-distance tick dispersal hosts) to resource-rich areas during their spring migration and the mate-finding Allee effect in tick population dynamics are key drivers for the spread of infected blacklegged ticks. The modeled increases in temperature extended the climatically suitable areas of Canada for infected blacklegged ticks and uninfected lone star ticks towards higher latitudes by up to 31% and 1%, respectively, and with an average predicted speed of the range expansion reaching 61 km/year and 23 km/year, respectively. Differences in the projected spatial distribution patterns of these tick species were due to differences in climate envelopes of tick populations, as well as the availability and attractiveness of suitable habitats for migratory birds. Our results indicate that the northward invasion process of lone star ticks is primarily driven by local dispersal of resident terrestrial hosts, whereas that of blacklegged ticks is governed by long-distance migratory bird dispersal. The results also suggest that mechanistic movement models provide a powerful approach for predicting tick-borne disease risk patterns under complex scenarios of climate, socioeconomic and land use/land cover changes.
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Background: Mass gatherings (MGs; eg, religious, sporting, musical, sociocultural, and other occasions that draw large crowds) pose public health challenges and concerns related to global health. A leading global concern regarding MGs is the possible importation and exportation of infectious diseases as they spread from the attendees to the general population, resulting in epidemic outbreaks. Governments and health authorities use technological interventions to support public health surveillance and prevent and control infectious diseases. Objective: This study aims to review the evidence on the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MG events. Methods: A systematic literature search was conducted in January 2022 using the Ovid MEDLINE, Embase, CINAHL, and Scopus databases to examine relevant articles published in English up to January 2022. Interventional studies describing or evaluating the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs were included in the analysis. Owing to the lack of appraisal tools for interventional studies describing and evaluating public health digital surveillance systems at MGs, a critical appraisal tool was developed and used to assess the quality of the included studies. Results: In total, 8 articles were included in the review, and 3 types of MGs were identified: religious (the Hajj and Prayagraj Kumbh), sporting (the Olympic and Paralympic Games, the Federation International Football Association World Cup, and the Micronesian Games), and cultural (the Festival of Pacific Arts) events. In total, 88% (7/8) of the studies described surveillance systems implemented at MG events, and 12% (1/8) of the studies described and evaluated an enhanced surveillance system that was implemented for an event. In total, 4 studies reported the implementation of a surveillance system: 2 (50%) described the enhancement of the system that was implemented for an event, 1 (25%) reported a pilot implementation of a surveillance system, and 1 (25%) reported an evaluation of an enhanced system. The types of systems investigated were 2 syndromic, 1 participatory, 1 syndromic and event-based, 1 indicator- and event-based, and 1 event-based surveillance system. In total, 62% (5/8) of the studies reported timeliness as an outcome generated after implementing or enhancing the system without measuring its effectiveness. Only 12% (1/8) of the studies followed the Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems and the outcomes of enhanced systems based on the systems' attributes to measure their effectiveness. Conclusions: On the basis of the review of the literature and the analysis of the included studies, there is limited evidence of the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs because of the absence of evaluation studies.
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Over the last decades, an increase in the emergence or re-emergence of arthropod-borne viruses has been observed in many regions. Viruses such as dengue, yellow fever, or zika are a threat for millions of people on different continents. On the other hand, some arboviruses are still described as endemic, however, they could become more important in the near future. Additionally, there is a group of arboviruses that, although important for animal breeding, are not a direct threat for human health. Those include, e.g., Schmallenberg, bluetongue, or African swine fever viruses. This review focuses on arboviruses and their major vectors: mosquitoes, ticks, biting midges, and sandflies. We discuss the current knowledge on arbovirus transmission, ecology, and methods of prevention. As arboviruses are a challenge to both human and animal health, successful prevention and control are therefore only possible through a One Health perspectiv
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Background: Forecasting the behavior of epidemic outbreaks is vital in public health. This makes it possible to anticipate the planning and organization of the health system, as well as possible restrictive or preventive measures. During the COVID-19 pandemic, this need for prediction has been crucial. This paper attempts to characterize the alternative models that were applied in the first wave of this pandemic context, trying to shed light that could help to understand them for future practical applications. Methods: A systematic literature search was performed in standardized bibliographic repertoires, using keywords and Boolean operators to refine the findings, and selecting articles according to the main PRISMA 2020 statement recommendations. Results: After identifying models used throughout the first wave of this pandemic (between March and June 2020), we begin by examining standard data-driven epidemiological models, including studies applying models such as SIR (Susceptible-Infected-Recovered), SQUIDER, SEIR, time-dependent SIR, and other alternatives. For data-driven methods, we identify experiences using autoregressive integrated moving average (ARIMA), evolutionary genetic programming machine learning, short-term memory (LSTM), and global epidemic and mobility models. Conclusions: The COVID-19 pandemic has led to intensive and evolving use of alternative infectious disease prediction models. At this point it is not easy to decide which prediction method is the best in a generic way. Moreover, although models such as the LSTM emerge as remarkably versatile and useful, the practical applicability of the alternatives depends on the specific context of the underlying variable and on the information of the target to be prioritized. In addition, the robustness of the assessment is conditioned by heterogeneity in the quality of information sources and differences in the characteristics of disease control interventions. Further comprehensive comparison of the performance of models in comparable situations, assessing their predictive validity, is needed. This will help determine the most reliable and practical methods for application in future outbreaks and eventual pandemics.
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Europeans are not only exposed to direct effects from climate change, but also vulnerable to indirect effects from infectious disease, many of which are climate sensitive, which is of concern because of their epidemic potential. Climatic conditions have facilitated vector-borne disease outbreaks like chikungunya, dengue, and West Nile fever and have contributed to a geographic range expansion of tick vectors that transmit Lyme disease and tick-borne encephalitis. Extreme precipitation events have caused waterborne outbreaks and longer summer seasons have contributed to increases in foodborne diseases. Under the Green Deal, The European Union aims to support climate change health policy, in order to be better prepared for the next health security threat, particularly in the aftermath of the traumatic COVID-19 experience. To bolster this policy process we discuss climate change-related hazards, exposures and vulnerabilities to infectious disease and describe observed impacts, projected risks, with policy entry points for adaptation to reduce these risks or avoid them altogether.
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Mosquito-borne disease (MBD) control depends largely on a range of public health measures aimed at reducing the spread of infected mosquitoes and human-mosquito contact. These public health measures are generally driven by voluntary, though in few occasions obligatory (e.g., indoor residual spraying), self-protective behaviors by individuals and communities. To develop effective interventions that promote public health measures, the underlying mechanisms that contribute to self-protective behaviors should be well understood. The present scoping review aims to provide a timely overview of how behavior change theories have been applied in the context of MBD control. In addition, the review proposes an integrated model that includes identified key determinants in MBD control behavior, and identifies knowledge gaps to inform future research. A comprehensive search was performed in several databases: MEDLINE, PsycINFO, Embase (Ovid), Web of Science Core Collection, CINAHL, ERIC, and Econ.Lit (EBSCO), as well as registered trials and reviews in CENTRAL and PROSPERO to identify ongoing or unpublished studies. References of included studies and literature reviews were screened, as well as citation tracking in Web of Science, Google Scholar and the malaria database of Behavior Change Impact. This scoping review identified a total of 28 studies. Most studies targeted personal-protective behavioral measures such as adopting, using, or maintaining insecticide-treated bed nets, and were most frequently informed by risk-related behavioral theories. Knowledge and perceived susceptibility of the risk, and related perceived efficacy were identified as key behavioral determinants in the conceptual, integrated human behavior model for MBD control. Numerous studies related to MBD control behavior, especially those focusing on knowledge-attitudes-practices (KAP), often lack a solid theoretical framework, which risks depicting an incomplete understanding of behaviors. In addition, by incorporating various behavioral disciplines into the domain of MBD control, a more comprehensive understanding of key behavioral determinants may be developed and applied in future research and MBD control efforts.
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Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health-Climate Risk framework.
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Climate change refers to the long-term changes in temperature and weather due to human activities. Increase in average global temperature and extreme and unpredictable weather are the most common manifestations of climate change. In recent years, it has acquired the importance of global emergency and affecting not only the wellbeing of humans but also the sustainability of other lifeforms. Enormous increase in the emission of greenhouse gases (CO2, methane and nitrous oxide) in recent decades largely due to burning of coal and fossil fuels, and deforestation are the main drivers of climate change. Marked increase in the frequency and intensity of natural disasters, rise in sea level, decrease in crop productivity and loss of biodiversity are the main consequences of climate change. Obvious mitigation measures include significant reduction in the emission of greenhouse gases and increase in the forest cover of the landmass. Conference of Parties (COP 21), held in Paris in 2015 adapted, as a legally binding treaty, to limit global warming to well below 2 °C, preferably to 1.5 °C by 2100, compared to pre-industrial levels. However, under the present emission scenario, the world is heading for a 3–4 °C warming by the end of the century. This was discussed further in COP 26 held in Glasgow in November 2021; many countries pledged to reach net zero carbon emission by 2050 and to end deforestation, essential requirements to keep 1.5 °C target. However, even with implementation of these pledges, the rise is expected to be around 2.4 °C. Additional measures are urgently needed to realize the goal of limiting temperature rise to 1.5 °C and to sustain biodiversity and human welfare.