Rift Valley Fever: An Emerging Mosquito-Borne Disease.

Rift Valley fever (RVF), an emerging mosquito-borne zoonotic infectious viral disease caused by the RVF virus (RVFV) (Bunyaviridae: Phlebovirus), presents significant threats to global public health and agriculture in Africa and the Middle East. RVFV is listed as a select agent with significant potential for international spread and use in bioterrorism. RVFV has caused large, devastating periodic epizootics and epidemics in Africa over the past ∼60 years, with severe economic and nutritional impacts on humans from illness and livestock loss. In the past 15 years alone, RVFV caused tens of thousands of human cases, hundreds of human deaths, and more than 100,000 domestic animal deaths. Cattle, sheep, goats, and camels are particularly susceptible to RVF and serve as amplifying hosts for the virus. This review highlights recent research on RVF, focusing on vectors and their ecology, transmission dynamics, and use of environmental and climate data to predict disease outbreaks. Important directions for future research are also discussed.

The increasing threat of Rift Valley fever virus globalization: strategic guidance for protection and preparation.

Rift Valley fever virus (RVFV) (Bunyavirales: Phlebovirus) is a prominent vector-borne zoonotic disease threat to global agriculture and public health. Risks of introduction into nonendemic regions are tied to changing climate regimes and other dynamic environmental factors that are becoming more prevalent, as well as virus evolutionary factors and human/animal movement. Endemic to the African continent, RVFV has caused large epizootics at the decadal scale since the early 20th century but has spread to the Arabian Peninsula and shows increasing patterns of interepizootic transmission on the annual scale. This virus can be transmitted by mosquitoes as well as through direct contact with infected tissues and can cause sporadic to widespread morbidity and mortality in domestic ungulate livestock as well as humans. High viremias in infected livestock moved for legal and illegal trade as well as in infected mosquitoes or human travelers can spread this virus worldwide. With increasing global commerce, it is likely RVFV will be introduced to new areas with suitable hosts, mosquito vector species, and environments. However, the strong mosquito component of RVFV epidemiology combined with advancements in vaccines, diagnostics, and virus evolutionary factors create opportunities for strategies to leverage models of connectivity among potential source and emerging regions to target surveillance and mitigation activities to reduce the risk of RVFV introduction, or contain the virus should it be introduced, into new regions.

A geopositioned and evidence-graded pan-species compendium of Mayaro virus occurrence.

Mayaro Virus (MAYV) is an emerging health threat in the Americas that can cause febrile illness as well as debilitating arthralgia or arthritis. To better understand the geographic distribution of MAYV risk, we developed a georeferenced database of MAYV occurrence based on peer-reviewed literature and unpublished reports. Here we present this compendium, which includes both point and polygon locations linked to occurrence data documented from its discovery in 1954 until 2022. We describe all methods used to develop the database including data collection, georeferencing, management and quality-control. We also describe a customized grading system used to assess the quality of each study included in our review. The result is a comprehensive, evidence-graded database of confirmed MAYV occurrence in humans, non-human animals, and arthropods to-date, containing 262 geo-positioned occurrences in total. This database - which can be updated over time - may be useful for local spill-over risk assessment, epidemiological modelling to understand key transmission dynamics and drivers of MAYV spread, as well as identification of major surveillance gaps.

Prediction of a Rift Valley fever outbreak.

El Niño/Southern Oscillation related climate anomalies were analyzed by using a combination of satellite measurements of elevated sea-surface temperatures and subsequent elevated rainfall and satellite-derived normalized difference vegetation index data. A Rift Valley fever (RVF) risk mapping model using these climate data predicted areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. To our knowledge, this is the first prospective prediction of a RVF outbreak.

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks.

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program's ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

Correction: Reanalysis of the 2000 Rift Valley fever outbreak in Southwestern Arabia.

[This corrects the article DOI: 10.1371/journal.pone.0233279.].

Impact of recent climate extremes on mosquito-borne disease transmission in Kenya.

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983-2019 for rainfall, 2000-2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.

A systematic review and meta-analysis of the potential non-human animal reservoirs and arthropod vectors of the Mayaro virus.

Improving our understanding of Mayaro virus (MAYV) ecology is critical to guide surveillance and risk assessment. We conducted a PRISMA-adherent systematic review of the published and grey literature to identify potential arthropod vectors and non-human animal reservoirs of MAYV. We searched PubMed/MEDLINE, Embase, Web of Science, SciELO and grey-literature sources including PAHO databases and dissertation repositories. Studies were included if they assessed MAYV virological/immunological measured occurrence in field-caught, domestic, or sentinel animals or in field-caught arthropods. We conducted an animal seroprevalence meta-analysis using a random effects model. We compiled granular georeferenced maps of non-human MAYV occurrence and graded the quality of the studies using a customized framework. Overall, 57 studies were eligible out of 1523 screened, published between the years 1961 and 2020. Seventeen studies reported MAYV positivity in wild mammals, birds, or reptiles and five studies reported MAYV positivity in domestic animals. MAYV positivity was reported in 12 orders of wild-caught vertebrates, most frequently in the orders Charadriiformes and Primate. Sixteen studies detected MAYV in wild-caught mosquito genera including Haemagogus, Aedes, Culex, Psorophora, Coquillettidia, and Sabethes. Vertebrate animals or arthropods with MAYV were detected in Brazil, Panama, Peru, French Guiana, Colombia, Trinidad, Venezuela, Argentina, and Paraguay. Among non-human vertebrates, the Primate order had the highest pooled seroprevalence at 13.1% (95% CI: 4.3-25.1%). From the three most studied primate genera we found the highest seroprevalence was in Alouatta (32.2%, 95% CI: 0.0-79.2%), followed by Callithrix (17.8%, 95% CI: 8.6-28.5%), and Cebus/Sapajus (3.7%, 95% CI: 0.0-11.1%). We further found that MAYV occurs in a wide range of vectors beyond Haemagogus spp. The quality of evidence behind these findings was variable and prompts calls for standardization of reporting of arbovirus occurrence. These findings support further risk emergence prediction, guide field surveillance efforts, and prompt further in-vivo studies to better define the ecological drivers of MAYV maintenance and potential for emergence.

Climate Conditions During a Rift Valley Fever Post-epizootic Period in Free State, South Africa, 2014-2019.

Rift Valley fever virus (RVFV) activity in Southern Africa tends to occur during periods of sustained elevated rainfall, cooler than normal conditions, and abundant vegetation cover creating ideal conditions for the increase and propagation of populations of RVFV mosquito vectors. These climatic and ecological conditions are modulated by large-scale tropical-wide El Niño-Southern Oscillation (ENSO) phenomena. The aim of this 5-year study was to investigate climatic conditions during Rift Valley fever "post-epizootic" period in Free State province of the Republic of South Africa, which historically experienced the largest RVF outbreaks in this country. We collected satellite-derived rainfall, land surface temperature (LST), and normalized difference vegetation index (NDVI) data since 2014 to understand broad environmental conditions in the years following a period of sustained and widespread large RVF outbreaks (2008-2011) in the region. We found this post-epizootic/interepizootic period to be characterized by below-normal rainfall (~-500 mm), above LSTs (~+12°C), depressed NDVI (60% below normal), and severe drought as manifested particularly during the 2015-2016 growing season. Such conditions reduce the patchwork of appropriate habitats available for emergence of RVFV vectors and diminish chances of RVFV activity. However, the 2016-2017 growing season saw a marked return to somewhat wetter conditions without any reported RVFV transmission. In general, the aggregate vector collections during this 5-year period follow patterns observed in climate measurements. During the 2017-2018 growing season, late and seasonally above average rainfall resulted in a focal RVF outbreak in one location in the study region. This unanticipated event is an indicator of cryptic RVF activity during post-epizootic period and may be a harbinger of RVFV activity in the coming years.

Applying a One Health Approach in Global Health and Medicine: Enhancing Involvement of Medical Schools and Global Health Centers.

Background: Multidisciplinary and multisectoral approaches such as One Health and related concepts (e.g., Planetary Health, EcoHealth) offer opportunities for synergistic expertise to address complex health threats. The connections between humans, animals, and the environment necessitate collaboration among sectors to comprehensively understand and reduce risks and consequences on health and wellbeing. One Health approaches are increasingly emphasized for national and international plans and strategies related to zoonotic diseases, food safety, antimicrobial resistance, and climate change, but to date, the possible applications in clinical practice and benefits impacting human health are largely missing. Methods: In 2018 the "Application of the One Health Approach to Global Health Centers" conference held at the Albert Einstein College of Medicine convened experts involved in One Health policy and practice. The conference examined issues relevant to One Health approaches, sharing examples of challenges and successes to guide application to medical school curricula and clinical practice for human health. This paper presents a synthesis of conference proceedings, framed around objectives identified from presentations and audience feedback. Findings and Recommendations: The following objectives provide opportunities for One Health involvement and benefits for medical schools and global health centers by: 1) Improving One Health resource sharing in global health and medical education; 2) Creating pathways for information flow in clinical medicine and global health practice; 3) Developing innovative partnerships for improved health sector outcomes; and 4) Informing and empowering health through public outreach. These objectives can leverage existing resources to deliver value to additional settings and stakeholders through resource efficiency, more holistic and effective service delivery, and greater ability to manage determinants of poor health status. We encourage medical and global health educators, practitioners, and students to explore entry points where One Health can add value to their work from local to global scale.

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents.

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.

Species composition, larval habitats, seasonal occurrence and distribution of potential malaria vectors and associated species of Anopheles (Diptera: Culicidae) from the Republic of Korea.

BACKGROUND: Larval mosquito habitats of potential malaria vectors and related species of Anopheles from three provinces (Gyeonggi, Gyeongsangbuk, Chungcheongbuk Provinces) of the Republic of Korea were surveyed in 2007. This study aimed to determine the species composition, seasonal occurrence and distributions of Anopheles mosquitoes. Satellite derived normalized difference vegetation index data (NDVI) was also used to study the seasonal abundance patterns of Anopheles mosquitoes. METHODS: Mosquito larvae from various habitats were collected using a standard larval dipper or a white plastic larval tray, placed in plastic bags, and were preserved in 100% ethyl alcohol for species identification by PCR and DNA sequencing. The habitats in the monthly larval surveys included artificial containers, ground depressions, irrigation ditches, drainage ditches, ground pools, ponds, rice paddies, stream margins, inlets and pools, swamps, and uncultivated fields. All field-collected specimens were identified to species, and relationships among habitats and locations based on species composition were determined using cluster statistical analysis. RESULTS: In about 10,000 specimens collected, eight species of Anopheles belonging to three groups were identified: Hyrcanus Group - Anopheles sinensis, Anopheles kleini, Anopheles belenrae, Anopheles pullus, Anopheles lesteri, Anopheles sineroides; Barbirostris Group - Anopheles koreicus; and Lindesayi Group - Anopheles lindesayi japonicus. Only An. sinensis was collected from all habitats groups, while An. kleini, An. pullus and An. sineroides were sampled from all, except artificial containers. The highest number of Anopheles larvae was found in the rice paddies (34.8%), followed by irrigation ditches (23.4%), ponds (17.0%), and stream margins, inlets and pools (12.0%). Anopheles sinensis was the dominant species, followed by An. kleini, An. pullus and An. sineroides. The monthly abundance data of the Anopheles species from three locations (Munsan, Jinbo and Hayang) were compared against NDVI and NDVI anomalies. CONCLUSION: The species composition of Anopheles larvae varied in different habitats at various locations. Anopheles populations fluctuated with the seasonal dynamics of vegetation for 2007. Multi-year data of mosquito collections are required to provide a better characterization of the abundance of these insects from year to year, which can potentially provide predictive capability of their population density based on remotely sensed ecological measurements.

The relationship between mosquito abundance and rice field density in the Republic of Korea.

BACKGROUND: Japanese encephalitis virus (JEV), the causative agent of Japanese encephalitis (JE), is endemic to the Republic of Korea (ROK) where unvaccinated United States (U.S.) military Service members, civilians and family members are stationed. The primary vector of the JEV in the ROK is Culex tritaeniorhynchus. The ecological relationship between Culex spp. and rice fields has been studied extensively; rice fields have been shown to increase the prevalence of Cx. tritaeniorhynchus. This research was conducted to determine if the quantification of rice field land cover surrounding U.S. military installations in the ROK should be used as a parameter in a larger risk model that predicts the abundance of Cx. tritaeniorhynchus populations. Mosquito data from the U.S. Forces Korea (USFK) mosquito surveillance program were used in this project. The average number of female Cx. tritaeniorhynchus collected per trap night for the months of August and September, 2002-2008, was calculated. Rice fields were manually digitized inside 1.5 km buffer zones surrounding U.S. military installations on high-resolution satellite images, and the proportion of rice fields was calculated for each buffer zone. RESULTS: Mosquito data collected from seventeen sample sites were analyzed for an association with the proportion of rice field land cover. Results demonstrated that the linear relationship between the proportion of rice fields and mosquito abundance was statistically significant (R2 = 0.62, r = .79, F = 22.72, p < 0.001). CONCLUSIONS: The analysis presented shows a statistically significant linear relationship between the two parameters, proportion of rice field land cover and log10 of the average number of Cx. tritaeniorhynchus collected per trap night. The findings confirm that agricultural land cover should be included in future studies to develop JE risk prediction models for non-indigenous personnel living at military installations in the ROK.

Reanalysis of the 2000 Rift Valley fever outbreak in Southwestern Arabia.

The first documented Rift Valley hemorrhagic fever outbreak in the Arabian Peninsula occurred in northwestern Yemen and southwestern Saudi Arabia from August 2000 to September 2001. This Rift Valley fever outbreak is unique because the virus was introduced into Arabia during or after the 1997-1998 East African outbreak and before August 2000, either by wind-blown infected mosquitos or by infected animals, both from East Africa. A wet period from August 2000 into 2001 resulted in a large number of amplification vector mosquitoes, these mosquitos fed on infected animals, and the outbreak occurred. More than 1,500 people were diagnosed with the disease, at least 215 died, and widespread losses of domestic animals were reported. Using a combination of satellite data products, including 2 x 2 m digital elevation images derived from commercial satellite data, we show rainfall and potential areas of inundation or water impoundment were favorable for the 2000 outbreak. However, favorable conditions for subsequent outbreaks were present in 2007 and 2013, and very favorable conditions were also present in 2016-2018. The lack of subsequent Rift Valley fever outbreaks in this area suggests that Rift Valley fever has not been established in mosquito species in Southwest Arabia, or that strict animal import inspection and quarantine procedures, medical and veterinary surveillance, and mosquito control efforts put in place in Saudi Arabia following the 2000 outbreak have been successful. Any area with Rift Valley fever amplification vector mosquitos present is a potential outbreak area unless strict animal import inspection and quarantine proceedures are in place.

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa.

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd's risk of RVFV infection.

Selected wetland soil properties correlate to Rift Valley fever livestock mortalities reported in 2009-10 in central South Africa.

Outbreaks of Rift Valley fever have devastating impacts on ruminants, humans, as well as on regional and national economies. Although numerous studies on the impact and outbreak of Rift Valley fever exist, relatively little is known about the role of environmental factors, especially soil, on the aestivation of the virus. This study thus selected 22 sites for study in central South Africa, known to be the recurrent epicenter of widespread Rift Valley fever outbreaks in Southern Africa. Soils were described, sampled and analyzed in detail at each site. Of all the soil variables analyzed for, only eight (cation exchange capacity, exchangeable Ca2+, exchangeable K+, exchangeable Mg2+, soluble Ca2+, medium sand, As, and Br) were statistically identified to be potential indicators of sites with reported Rift Valley fever mortalities, as reported for the 2009-2010 Rift Valley fever outbreak. Four soil characteristics (exchangeable K+, exchangeable Mg2+, medium sand, and Br) were subsequently included in a discriminant function that could potentially be used to predict sites that had reported Rift Valley fever-associated mortalities in livestock. This study therefore constitutes an initial attempt to predict sites prone to Rift Valley fever livestock mortality from soil properties and thus serves as a basis for broader research on the interaction between soil, mosquitoes and Rift Valley fever virus. Future research should include other environmental components such as vegetation, climate, and water properties as well as correlating soil properties with floodwater Aedes spp. abundance and Rift Valley fever virus prevalence.

Author Correction: Global disease outbreaks associated with the 2015-2016 El Niño Event.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Transdisciplinary Research Priorities for Human and Planetary Health in the Context of the 2030 Agenda for Sustainable Development.

Human health and wellbeing and the health of the biosphere are inextricably linked. The state of Earth's life-support systems, including freshwater, oceans, land, biodiversity, atmosphere, and climate, affect human health. At the same time, human activities are adversely affecting natural systems. This review paper is the outcome of an interdisciplinary workshop under the auspices of the Future Earth Health Knowledge Action Network (Health KAN). It outlines a research agenda to address cross-cutting knowledge gaps to further understanding and management of the health risks of these global environmental changes through an expert consultation and review process. The research agenda has four main themes: (1) risk identification and management (including related to water, hygiene, sanitation, and waste management); food production and consumption; oceans; and extreme weather events and climate change. (2) Strengthening climate-resilient health systems; (3) Monitoring, surveillance, and evaluation; and (4) risk communication. Research approaches need to be transdisciplinary, multi-scalar, inclusive, equitable, and broadly communicated. Promoting resilient and sustainable development are critical for achieving human and planetary health.

Predicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vector.

Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic arbovirus with important livestock and human health, and economic consequences across Africa and the Arabian Peninsula. Climate and vegetation monitoring guide RVFV forecasting models and early warning systems; however, these approaches make monthly predictions and a need exists to predict primary vector abundances at finer temporal scales. In Kenya, an important primary RVFV vector is the mosquito Aedes mcintoshi. We used a zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae. mcintoshi mosquito counts and remotely sensed climate and topographic variables to predict where and when abundances would be high in Kenya and western Somalia. The data supported a positive effect on abundance of minimum wetness index values within 500 m of a sampling site, cumulative precipitation values 0 to 14 days prior to sampling, and elevated land surface temperature values ~3 weeks prior to sampling. The probability of structural zero counts of mosquitoes increased as percentage clay in the soil decreased. Weekly retrospective predictions for unsampled locations across the study area between 1 September and 25 January from 2002 to 2016 predicted high abundances prior to RVFV outbreaks in multiple foci during the 2006-2007 epizootic, except for two districts in Kenya. Additionally, model predictions supported the possibility of high Ae. mcintoshi abundances in Somalia, independent of Kenya. Model-predicted abundances were low during the 2015-2016 period when documented outbreaks did not occur, although several surveillance systems issued warnings. Model predictions prior to the 2018 RVFV outbreak indicated elevated abundances in Wajir County, Kenya, along the border with Somalia, but RVFV activity occurred west of the focus of predicted high Ae. mcintoshi abundances.

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event.

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015-2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14-81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5-28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.