An official website of the United States government
A comprehensive approach to integrated one health surveillance and responseSurveillance data plays a crucial role in understanding and responding to emerging infectious diseases; here, we learn why adopting a One Health surveillance approach to EIDs can help to protect human, animal, and environmental health. Over 75% of emerging infectious diseases (EIDs) affecting humans are zoonotic diseases with animal hosts, which can be transmitted by waterborne, foodborne, vector-borne, or air-borne pathways. (7) Early detection is important and allows for a rapid response through preventive and control measures. However, early detection of EIDs is hindered by several obstacles, such as climate change, which can alter habitats, leading to shifts in the distribution of disease- carrying vectors like mosquitoes and ticks. This can result in diseases such as malaria, dengue fever, and Lyme disease becoming more common in areas with established transmission or spreading to new areas entirely. (4) Environmental changes such as deforestation and urbanization disrupt ecosystems, increasing the likelihood of zoonotic disease spillover from wildlife to humans. In addition to working at the interface of these changes, detection and tracking of EIDs also requires sharing and standardization of complex data and integrating processes across different regions and health systems.
more »
« less
Climate change and infectious disease: a review of evidence and research trends
Abstract BackgroundClimate change presents an imminent threat to almost all biological systems across the globe. In recent years there have been a series of studies showing how changes in climate can impact infectious disease transmission. Many of these publications focus on simulations based on in silico data, shadowing empirical research based on field and laboratory data. A synthesis work of empirical climate change and infectious disease research is still lacking. MethodsWe conducted a systemic review of research from 2015 to 2020 period on climate change and infectious diseases to identify major trends and current gaps of research. Literature was sourced from Web of Science and PubMed literary repositories using a key word search, and was reviewed using a delineated inclusion criteria by a team of reviewers. ResultsOur review revealed that both taxonomic and geographic biases are present in climate and infectious disease research, specifically with regard to types of disease transmission and localities studied. Empirical investigations on vector-borne diseases associated with mosquitoes comprised the majority of research on the climate change and infectious disease literature. Furthermore, demographic trends in the institutions and individuals published revealed research bias towards research conducted across temperate, high-income countries. We also identified key trends in funding sources for most resent literature and a discrepancy in the gender identities of publishing authors which may reflect current systemic inequities in the scientific field. ConclusionsFuture research lines on climate change and infectious diseases should considered diseases of direct transmission (non-vector-borne) and more research effort in the tropics. Inclusion of local research in low- and middle-income countries was generally neglected. Research on climate change and infectious disease has failed to be socially inclusive, geographically balanced, and broad in terms of the disease systems studied, limiting our capacities to better understand the actual effects of climate change on health. Graphical abstract
more »
« less
- Award ID(s):
- 2116748
- PAR ID:
- 10413923
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Infectious Diseases of Poverty
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2049-9957
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract BackgroundVector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. MethodsTo better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. ResultsModels based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. ConclusionsHotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.more » « less
-
Abstract BackgroundNeglected tropical diseases affect the most vulnerable populations and cause chronic and debilitating disorders. Socioeconomic vulnerability is a well-known and important determinant of neglected tropical diseases. For example, poverty and sanitation could influence parasite transmission. Nevertheless, the quantitative impact of socioeconomic conditions on disease transmission risk remains poorly explored. MethodsThis study investigated the role of socioeconomic variables in the predictive capacity of risk models of neglected tropical zoonoses using a decade of epidemiological data (2007–2018) from Brazil. Vector-borne diseases investigated in this study included dengue, malaria, Chagas disease, leishmaniasis, and Brazilian spotted fever, while directly-transmitted zoonotic diseases included schistosomiasis, leptospirosis, and hantaviruses. Environmental and socioeconomic predictors were combined with infectious disease data to build environmental and socioenvironmental sets of ecological niche models and their performances were compared. ResultsSocioeconomic variables were found to be as important as environmental variables in influencing the estimated likelihood of disease transmission across large spatial scales. The combination of socioeconomic and environmental variables improved overall model accuracy (or predictive power) by 10% on average (P < 0.01), reaching a maximum of 18% in the case of dengue fever. Gross domestic product was the most important socioeconomic variable (37% relative variable importance, all individual models exhibitedP < 0.00), showing a decreasing relationship with disease indicating poverty as a major factor for disease transmission. Loss of natural vegetation cover between 2008 and 2018 was the most important environmental variable (42% relative variable importance,P < 0.05) among environmental models, exhibiting a decreasing relationship with disease probability, showing that these diseases are especially prevalent in areas where natural ecosystem destruction is on its initial stages and lower when ecosystem destruction is on more advanced stages. ConclusionsDestruction of natural ecosystems coupled with low income explain macro-scale neglected tropical and zoonotic disease probability in Brazil. Addition of socioeconomic variables improves transmission risk forecasts on tandem with environmental variables. Our results highlight that to efficiently address neglected tropical diseases, public health strategies must target both reduction of poverty and cessation of destruction of natural forests and savannas.more » « less
-
Purpose of Review: In this paper, we synthesize the status and trends of studies assessing the effects of landscape structure and changes on zoonotic and vector-borne disease risk in the Tropical America region (i.e., spanning from Mexico to southern South America). Understanding how landscape structure affects disease emergence is critical to designing prevention measures and maintaining healthy ecosystems for both animals and humans. Recent Findings: We found that there is a small number of articles being published each year regarding landscape structure and zoonotic and vector borne diseases in the Tropical Americas region, with a slight growing trend after 2013. We identified a large knowledge gap on the subject in most of the countries: in 15 of 27 countries, no article was found, and 72% of the current literature available is concentrated in only three countries (Brazil, Panama, and Colombia). Five diseases represent about 68% of the available knowledge, which compared to over 200 types of known zoonoses and vector-borne diseases, is an extremely low number. Most of the knowledge that exists for the region is about landscape composition, with few studies evaluating configuration parameters. Summary: In general, landscape changes presented a positive effect on zoonotic and disease risk in most of the studies found, with habitat loss, fragmentation and increases in the amount of edge habitats leading to an increased risk of the diseases investigated. The continued integration of landscape ecology into disease ecology studies can increase the knowledge about how land use change is affecting animals and human health and can allow the establishment of guidelines to create landscapes that have a low pathogenicity.more » « less
-
Abstract The transmission of vector-borne diseases is governed by complex factors including pathogen characteristics, vector–host interactions, and environmental conditions. Temperature is a major driver for many vector-borne diseases including Bluetongue viral (BTV) disease, a midge-borne febrile disease of ruminants, notably livestock, whose etiology ranges from mild or asymptomatic to rapidly fatal, thus threatening animal agriculture and the economy of affected countries. Using modeling tools, we seek to predict where the transmission can occur based on suitable temperatures for BTV. We fit thermal performance curves to temperature-sensitive midge life-history traits, using a Bayesian approach. We incorporate these curves into S ( T ), a transmission suitability metric derived from the disease’s basic reproductive number, $$R_0.$$ R 0 . This suitability metric encompasses all components that are known to be temperature-dependent. We use trait responses for two species of key midge vectors, Culicoides sonorensis and Culicoides variipennis present in North America. Our results show that outbreaks of BTV are more likely between 15 $$^{\circ }$$ ∘ C and $$34^{\circ }\hbox { C}$$ 34 ∘ C , with predicted peak transmission risk at 26 $$^\circ$$ ∘ C. The greatest uncertainty in S ( T ) is associated with the following: the uncertainty in mortality and fecundity of midges near optimal temperature for transmission; midges’ probability of becoming infectious post-infection at the lower edge of the thermal range; and the biting rate together with vector competence at the higher edge of the thermal range. We compare three model formulations and show that incorporating thermal curves into all three leads to similar BTV risk predictions. To demonstrate the utility of this modeling approach, we created global suitability maps indicating the areas at high and long-term risk of BTV transmission, to assess risk and to anticipate potential locations of disease establishment.more » « less
