43 research outputs found
Building urban climate resilience through public health: Identifying strategies for integrated public health governance in Duran, Ecuador
In the poster it is presented the Case Study of Duran, Ecuador, a coastal city of 235.000 inhabitants which are exposed to annual flooding events that increase the risk of vector-borne and other infectious diseases. Duran is an in-dustrial satellite city of Guayaquil, the largest city of Ecuador, with a rapid population growth that lead to a large area of informal settle-ments on the city. Applying an integrated climate risk management and urban health focus, it is assessed the Duran strategies for reducing vulnerability to flooding, landslides and heat waves through a collabo-rative inter-sectoral approach among the health, urban, and scientific actors. Stakeholder engagement between municipality and researchers are providing evidence and building knowledge to implement “low re-gret” adaptation strategies and community active participation
An Operational Framework for Urban Vulnerability to Floods in the Guayas Estuary Region: The Duran Case Study
Duran is a coastal city located in the Guayas Estuary region in which 24% of urban sectors suffers from the effects of chronic flooding. This study seeks to assess the causes of Duran’s vulnerability by considering exposure, population sensitivity and adaptive capacity to establish alternatives to reduce its vulnerability to flooding. An operational framework is proposed based on the vulnerability definition of the Intergovernmental Panel on Climate Change (IPCC) and applying a census-based Index of Vulnerability, a geographic information system and local knowledge of urban development. A Principal Component and equal weighting analysis were applied as well as a spatial clustering to explore the spatial vulnerability across the city. A total of 34% of the city area is mapped as having high and very high vulnerability, mostly occupied by informal settlements (e.g., 288 hectares). Underlying factors were poor quality housing, lack of city services and low adaptive capacity of the community. However, some government housing programs (e.g., El Recreo), with better housing and adaptive capacity were also highly vulnerable. Limited urban planning governance has led to the overloading of storm water and drainage infrastructure which cause chronic flooding. Understanding the underlying causes of vulnerability is critical in order develop integrated strategies that increase city resilience to climate change
Spatiotemporal clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in Machala, Ecuador, in 2010
Background: Dengue fever, a mosquito-borne viral disease, is a rapidly emerging public health problem in Ecuador and throughout the tropics. However, we have a limited understanding of the disease transmission dynamics in these regions. Previous studies in southern coastal Ecuador have demonstrated the potential to develop a dengue early warning system (EWS) that incorporates climate and non-climate information. The objective of this study was to characterize the spatiotemporal dynamics and climatic and social-ecological risk factors associated with the largest dengue epidemic to date in Machala, Ecuador, to inform the development of a dengue EWS. Methods: The following data from Machala were included in analyses: neighborhood-level georeferenced dengue cases, national census data, and entomological surveillance data from 2010; and time series of weekly dengue cases (aggregated to the city-level) and meteorological data from 2003 to 2012. We applied LISA and Moran’s I to analyze the spatial distribution of the 2010 dengue cases, and developed multivariate logistic regression models through a multi-model selection process to identify census variables and entomological covariates associated with the presence of dengue at the neighborhood level. Using data aggregated at the city-level, we conducted a time-series (wavelet) analysis of weekly climate and dengue incidence (2003-2012) to identify significant time periods (e.g., annual, biannual) when climate co-varied with dengue, and to describe the climate conditions associated with the 2010 outbreak. Results: We found significant hotspots of dengue transmission near the center of Machala. The best-fit model to predict the presence of dengue included older age and female gender of the head of the household, greater access to piped water in the home, poor housing condition, and less distance to the central hospital. Wavelet analyses revealed that dengue transmission co-varied with rainfall and minimum temperature at annual and biannual cycles, and we found that anomalously high rainfall and temperatures were associated with the 2010 outbreak. Conclusions: Our findings highlight the importance of geospatial information in dengue surveillance and the potential to develop a climate-driven spatiotemporal prediction model to inform disease prevention and control interventions. This study provides an operational methodological framework that can be applied to understand the drivers of local dengue risk
Climate services for health: predicting the evolution of the 2016 dengue season in Machala, Ecuador
Background
El Niño and its effect on local meteorological conditions potentially influences interannual variability in dengue transmission in southern coastal Ecuador. El Oro province is a key dengue surveillance site, due to the high burden of dengue, seasonal transmission, co-circulation of all four dengue serotypes, and the recent introduction of chikungunya and Zika. In this study, we used climate forecasts to predict the evolution of the 2016 dengue season in the city of Machala, following one of the strongest El Niño events on record.
Methods
We incorporated precipitation, minimum temperature, and Niño3·4 index forecasts in a Bayesian hierarchical mixed model to predict dengue incidence. The model was initiated on Jan 1, 2016, producing monthly dengue forecasts until November, 2016. We accounted for misreporting of dengue due to the introduction of chikungunya in 2015, by using active surveillance data to correct reported dengue case data from passive surveillance records. We then evaluated the forecast retrospectively with available epidemiological information.
Findings
The predictions correctly forecast an early peak in dengue incidence in March, 2016, with a 90% chance of exceeding the mean dengue incidence for the previous 5 years. Accounting for the proportion of chikungunya cases that had been incorrectly recorded as dengue in 2015 improved the prediction of the magnitude of dengue incidence in 2016.
Interpretation
This dengue prediction framework, which uses seasonal climate and El Niño forecasts, allows a prediction to be made at the start of the year for the entire dengue season. Combining active surveillance data with routine dengue reports improved not only model fit and performance, but also the accuracy of benchmark estimates based on historical seasonal averages. This study advances the state-of-the-art of climate services for the health sector, by showing the potential value of incorporating climate information in the public health decision-making process in Ecuador
Oceanography of Harmful Algal Blooms on the Ecuadorian Coast (1997–2017): Integrating Remote Sensing and Biological Data
Ocean climate drivers and phytoplankton life strategies interact in a complex dynamic to produce harmful algal blooms (HABs). This study aims to integrate historical biological data collected during “red tide” events along the Ecuadorian coast between 1997 and 2017 in relation to five ocean variables derived from satellite remote sensing data to explain the seasonal drivers of coastal processes associated with HABs dynamics. Seasonality of the occurrence of HABs was assessed in relation to oceanographic variables by applying multiple correspondence analysis (MCA) to the Ecuadorian central coast (Zone 1) and at the outer and inner Gulf of Guayaquil (Zone 2). Sixty-seven HABs events were registered between 1997 and 2017. From a total of 40 species of phytoplankton identified, 28 were identified as non-toxic and the remaining 12 are well known to produce toxins. Dinoflagellates were the taxonomic group most highly associated with potential HABs events along the entire Ecuadorian coast. HABs appear to be constrained by the Humboldt coastal upwelling, high precipitation, and associated coastal runoff, with higher biomass abundance in the Gulf of Guayaquil than in the central coast. Results from the MCA reveal that in the central Ecuadorian coast (oligotrophic system), toxic HABs occurred with low abundance of dinoflagellates, while in the Gulf of Guayaquil (eutrophic system), toxic HABs corresponded to a high abundance of dinoflagellates. In both cases, high values were found for sea surface temperature, precipitation, and irradiance—characteristic of wet seasons or El Niño years. Non-toxic HABs occurred with a high abundance of dinoflagellates, ciliates, and centric diatoms, corresponding to colder waters and low levels of precipitation and irradiance. These findings confirm that dinoflagellates display several strategies that enhance their productive capacity when ocean conditions are warmer, allowing them to produce toxins at high or at low concentrations. Considering that the Gulf of Guayaquil is essential to tourism, the shrimp industry, fisheries, and international shipping, these findings strongly suggest the need to establish an ecosystem health research program to monitor HABs and the development of a preventive policy for tourism and public health in Ecuador
Building resilience to mosquito-borne diseases in the Caribbean.
Small island developing states in the Caribbean are among the most vulnerable countries on the planet to climate variability and climate change. In the last 3 decades, the Caribbean region has undergone frequent and intense heat waves, storms, floods, and droughts. This has had a detrimental impact on population health and well-being, including an increase in infectious disease outbreaks. Recent advances in climate science have enhanced our ability to anticipate hydrometeorological hazards and associated public health challenges. Here, we discuss progress towards bridging the gap between climate science and public health decision-making in the Caribbean to build health system resilience to extreme climatic events. We focus on the development of climate services to help manage mosquito-transmitted disease epidemics. There are numerous areas of ongoing biological research aimed at better understanding the direct and indirect impacts of climate change on the transmission of mosquito-borne diseases. Here, we emphasise additional factors that affect our ability to operationalise this biological understanding. We highlight a lack of financial resources, technical expertise, data sharing, and formalised partnerships between climate and health communities as major limiting factors to developing sustainable climate services for health. Recommendations include investing in integrated climate, health and mosquito surveillance systems, building regional and local human resource capacities, and designing national and regional cross-sectoral policies and national action plans. This will contribute towards achieving the Sustainable Development Goals (SDGs) and maximising regional development partnerships and co-benefits for improved health and well-being in the Caribbean
The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador
Between October 2018 - May 2019, sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Niño event. In May 2019, the global El Niño Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns will persist at least until the end of the northern hemisphere summer. El Niño and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Niño for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicate that the mild and ongoing El Niño event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Niño event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region
Co-developing climate services for public health: Stakeholder needs and perceptions for the prevention and control of Aedes-transmitted diseases in the Caribbean.
BACKGROUND: Small island developing states (SIDS) in the Caribbean region are challenged with managing the health outcomes of a changing climate. Health and climate sectors have partnered to co-develop climate services to improve the management of emerging arboviral diseases such as dengue fever, for example, through the development of climate-driven early warning systems. The objective of this study was to identify health and climate stakeholder perceptions and needs in the Caribbean, with respect to the development of climate services for arboviruses. METHODS: Stakeholders included public decision makers and practitioners from the climate and health sectors at the regional (Caribbean) level and from the countries of Dominica and Barbados. From April to June 2017, we conducted interviews (n = 41), surveys (n = 32), and national workshops with stakeholders. Survey responses were tabulated, and audio recordings were transcribed and analyzed using qualitative coding to identify responses by research topic, country/region, and sector. RESULTS: Health practitioners indicated that their jurisdiction is currently experiencing an increased risk of arboviral diseases associated with climate variability, and most anticipated that this risk will increase in the future. National health sectors reported financial limitations and a lack of technical expertise in geographic information systems (GIS), statistics, and modeling, which constrained their ability to implement climate services for arboviruses. National climate sectors were constrained by a lack of personnel. Stakeholders highlighted the need to strengthen partnerships with the private sector, academia, and civil society. They identified a gap in local research on climate-arbovirus linkages, which constrained the ability of the health sector to make informed decisions. Strategies to strengthen the climate-health partnership included a top-down approach by engaging senior leadership, multi-lateral collaboration agreements, national committees on climate and health, and shared spaces of dialogue. Mechanisms for mainstreaming climate services for health operations to control arboviruses included climatic-health bulletins and an online GIS platform that would allow for regional data sharing and the generation of spatiotemporal epidemic forecasts. Stakeholders identified a 3-month forecast of arboviral illness as the optimal time frame for an epidemic forecast. CONCLUSIONS: These findings support the creation of interdisciplinary and intersectoral 'communities of practice' and the co-design of climate services for the Caribbean public health sector. By fostering the effective use of climate information within health policy, research and practice, nations will have greater capacity to adapt to a changing climate
Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents
Funding: J.M.C., A.D.L., E.F.L., and E.A.M. were supported by a Stanford Woods Institute for the Environment—Environmental Ventures Program grant (PIs: E.A.M., A.D.L., and E.F.L.). E.A.M. was also supported by a Hellman Faculty Fellowship and a Terman Award. A.D.L., B.A.N., F.M.M., E.N.G.S., M.S.S., A.R.K., R.D., A.A., and H.N.N. were supported by a National Institutes of Health R01 grant (AI102918; PI: A.D.L.). E.A.M., A.M.S.I., and S.J.R. were supported by a National Science Foundation (NSF) Ecology and Evolution of Infectious Diseases (EEID) grant (DEB-1518681), and A.M.S.I. and S.J.R. were also supported by an NSF DEB RAPID grant (1641145). E.A.M. was also supported by a National Institute of General Medical Sciences Maximizing Investigators’ Research Award grant (R35GM133439) and an NSF and Fogarty International Center EEID grant (DEB-2011147).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.Publisher PDFPeer reviewe
Locating Zika
The emergence of Zika virus challenged conventional ideas of mosquito-borne diseases, tested the resilience of health systems and embedded itself within local sociocultural worlds, with major implications for environmental, sexual, reproductive and paediatric health. This book explores this complex viral epidemic and situates it within its broader social, epidemiological and historical context in Latin America and the Caribbean. The chapters include a diverse set of case studies from scholars and health practitioners working across the region, from Brazil, Venezuela, Ecuador, Mexico, Colombia, the United States and Haiti. The book explores how mosquito-borne disease epidemics (not only Zika but also chikungunya, dengue and malaria) intersect with social change and health governance. By doing so, the authors reflect on the ways in which situated knowledge and social science approaches can contribute to more effective health