Objective: To show the epidemiological reports of the impact on health with local and global environmental change. Data sources: our main reports were measured with parameters like temperature and precipitations during 1950-2000; and climate change scenarios projected to 2020-2030-2050. Also, ozone like air pollutant, 2009 pandemic A/H1N1 spring outbreak; floodings and acute respiratory and diaorrheal infectious diseases, dermatitis and conjunctival diseases related with contaminated food, air, water and soil after intense rainfalls; surveillance of vibrio parahaemolyticus; ocean pH and enterococcus. Methods: Samples were obtained and sent to state public health laboratory in Morelia, Michoacan, Mexico. Meteorological reports were obtained and reviewed by the Delegational state of the National Commision of Water and analysed by the Athmosferic Science Center from the National University Autonomus of Mexico in Mexico City. Descriptive epidemiological reports were assessed to complete these reports from the epidemiological surveillance health system of Michoacan. Results: Acute infectious diseases were identified like A/H1N1 flu virus and ozone air pollutant in april and may in 2009. Respiratory and diaorrheal infectious outbreaks in heavy rainfalls and floodings in 2010 february in the Monarch butterfly biosphere region in East Michoacan. In the same year, in april an outbreak of vibrio parahaemolyticus were presented. And, recently in 2013 a serial reports related with a low level pH decrease in the Pacific ocean coast and the presence of enterococcus were measured. All these results were associated with temperature, precipitations and climate change scenarios since 1950-2000 and 2020, 2030 and 2050 measures in Michoacan. Conclusions: Climate change and its impact on human health is a global health concern. Acute and infectious diseases were identified in places where our temperature and precipitations are increasing like world reports in ar4 and ar5 IPCC and others epidemiological data have been publishing.
Why parasites harm their hosts is a central question in the study of host-parasite interactions. Since parasites must utilize host resources to increase their fitness, a virulence-transmission trade-off has been hypothesized, suggesting that increasing transmission rate comes at the cost of shorter duration of infection. While this trade-off has been explored in single-host systems, there have been few studies determining whether a parallel trade-off exists for multi-host parasites. The ability to utilize multiple hosts requires adaptations to a variety of host defenses and life histories. As the diversity of host species increases, the ability for a parasite to effectively utilize host resources may be reduced, resulting in reduced virulence for generalist parasites. However, as parasites infect novel hosts, they may be more likely to encounter naive hosts without evolved defences, which may lead to maladaptive virulence, such that parasites harm hosts to a greater degree than expected for optimal transmission. Virulence is difficult to estimate for natural host populations, but cases of reportable diseases in domesticated animals provide a unique opportunity to test these hypotheses. Using a Bayesian hierarchical framework, we examine global data from the World Organisation for Animal Health (OIE) on host mortality for diseases of domesticated mammals. By comparing alternate metrics of host specificity, we test for the first time how host diversity influences rates of parasite induced mortality. We believe the results of this study will have important ramifications for global health, as well as our understanding of parasite evolution in multi-host systems.
Dhaka, the largest cholera endemic megacity in the world, has seen a dramatic rise in patients seeking treatment for cholera and other diarrheal infections since 1980. While mortality has been checked to acceptable levels, disease burden has seen continuous increase in the form of both endemic and epidemic outbreaks. However, there has not been any systematic study on linking the long-term disease trends with changes in related climatic, environmental, or societal variables. More importantly, there have not been any systematic efforts in decision-making or collaboration between water management policies and disease prevention approaches.
One major bottleneck to investigate such changes has been the lack of continuous and reliable disease surveillance data. With the availability of detailed 30 years data on cholera incidence, we can now investigate the temporal and spatial changes in disease dynamics with respect to climatic and anthropogenic trends in the Dhaka region. Focusing on the previous three decades, the main objective of our study is to investigate the natural and human dimensions and interactions between the water and health sectors in the Dhaka City region.
While an endemic trend is getting stronger in the spring pre-monsoon season, the fall post-monsoon season shows increased variability and is epidemic in nature. The pre-monsoon dry season is potentially becoming the dominant cholera season of the year, followed by monsoon flood related propagation and cross-contamination in later months of the year. To date, there has not been any systematic study on linking the long-term disease trends with observed changes in hydroclimatic indicators. We focus on the dry and the wet season indicators individually, and develop trends of hydroclimatic extremes using a recently developed gridded data product – and compare with cholera patterns and regional hydrology, water access, and frequency of natural disasters.
The purpose of this paper is to offer reflections on conventional theories concerning causes and determinants of diseases. It also intends to examine both theoretical and empirical bases for adopting an Integrated Social-Ecological Systems (ISES) lens to comprehend complexities related to drivers, determinants and causes of dengue disease. We assessed the entomological, serological, and social aspects of dengue transmission in the complex urban background in Dhaka. Within this study an emphasis has been placed on illustrating how feedback loops and non-linearity-functions in system have a direct bearing upon various aspects of disease occurrences. We performed the entomological and serological surveys during pre-monsoon and post-monsoon periods among 1200 households for three consecutive years (i.e., 2011-2013) in 12 selected city wards in Dhaka. Same households were visited repeatedly to estimate dengue seroconversion in the city which was done first time in Bangladesh context in this study. Findings of this study revealed that most of the Dhaka city population were exposed to dengue serotypes and stegomyia indices were also high compare to other south Asian countries. Social survey of the 300 people revealed the miscommunication about dengue disease and need for strategic risk communication to the city population. Our study advances the theoretical as well as empirical basis for considering an integrated human-nature systems approach to explaining disease occurrence at all levels so that factors at the individual, household/neighbourhood, and regional levels are not studied in isolation.
In collaboration with the City of Brownsville, Texas, our geospatial research combined with socioeconomic factors will deliver an Aedes mosquito hot-spot map to enable Brownsville Department of Public Health to deliver more effective integrated mosquito management, and to reduce public health exposure to potential Zika, Dengue fever and Chikungunya viruses. Vector-borne disease risk in the United States is expected to increase and spread north with a warming climate. Brownsville, TX is a US-Mexico border city with a history of dengue outbreaks and as of January 2017 had six locally transmitted cases of Zika virus (ZIKV). Aedes aegypti and Ae. albopictus mosquitos are the primary ZIKV vectors. The research is based on analysis of socioeconomic and environmental determinants of Aedes habitat and mosquito trap data. Specifically, we used aerial photography and lidar elevation data to create a novel one meter resolution land cover map to characterize the physical environment of Brownsville at the neighborhood scale where vector control is most effective. We created a detailed topographic map from lidar data to highlight potential depressions capable of providing temporary breeding habitat, and used historical mosquito trap data to illuminate patterns of Aedes mosquito abundance. We mapped multiple socioeconomic variables that may contribute to exposure risk, including age of housing structures and income. This indicated which neighborhoods may contain higher porosity structures, or populations more likely to rely on open windows for cooling rather than air conditioning, both creating greater opportunity for mosquito contact. The goal is to identify environmental determinants that create suitable Aedes mosquito habitat and harborage, and the socioeconomic determinants that may increase exposure risk for certain populations. Here we report the data and design behind our efforts, and initial results for Aedes hot-spots and mosquito control in the study area.
(Re)emergence of pathogens under enhanced climatic variability pose a threat to human population. With global circulation of pathogens, now possible, and curious case of emergence of Zika Virus in Latin America in 2015, there is a strong need to develop quick and efficient protocol(s) for predicting ecological niches of pathogens. One of the biggest challenges is to obtain health data, which is often not available at appropriate times, therefore limiting our ability to develop any algorithms on prediction of infectious diseases (e.g., cholera in Haiti, Ebola in West Africa or Zika in Latin America). Here, we present a perspective and discussion on how satellites in combination to big data mechanisms can be used to decipher limited information from internet and available literature, and thereafter can produce an ensemble of predictive risks of outbreak of disease. We will present example from our previous research on cholera, Zika, Dengue and Chikungunya from several parts of the globe and will show how long term implementation of satellite data can be useful for public health under changing climate conditions.
Diarrheal diseases continue to pose a severe health threat in regions where sanitation facilities remain marginal and are prone to destruction. Drastic changes in water environment due to the Hurricane Matthew, and damage to the inferior and fragile water and sanitation infrastructure has created an urgent public health emergency in terms of looming disease outbreaks in Haiti. With limited efficacy of vaccines, it is important to device alternate methods to determine environmental conditions favorable for diarrheal diseases. Hydroclimatic processes, primarily precipitation and temperature are found to be strongly associated with epidemic and episodic outbreak of cholera. Here, using cholera as one of the signature diarrheal disease, we present a framework integrating hydro-climatic and social understanding following a natural disaster e.g. Hurricane Matthew. With satellite based near real time (NRT) precipitation and gridded temperature, data on the hurricane path, and water and sanitation (WASH) infrastructure, we tracked changing environmental conditions for growth of pathogenic vibrios, and predicted and validated risk of cholera infection immediately after hurricane. Risks of cholera in South Western part of Haiti are sufficiently high since November 2016 and coming months. The findings of this study provide a contemporary basis to monitor ground conditions and guide public health interventions to control cholera (through vaccines and/or oral rehydration, as well as strengthening WASH infrastructure). Cholera forecasting capacity based on NRT precipitation monitoring will be extremely valuable – especially for 2017 rainy season, assuming social and behavioral disruption from the Hurricane Matthew.
In 2015, building on decades-long efforts by environmental and other scientists to address the impacts of anthropogenic-related climate change on human health, a Lancet-Rockefeller Planetary Health Commission published a report calling for collaboration across multiple disciplines to confront escalating threats to the health of the Earth and its ecosystems that underpin the sustainability, health and well-being of humans and other species. The Planetary Health Alliance (PHA) was established to marshal the forces of academia, governments, and non-governmental organizations to address the threats and achieve the goals and objectives described in the Report. In the late 1990s, a slowly evolving One-Health initiative, aimed at bringing “multiple disciplines to work together, locally, nationally, and internationally, to achieve optimal health of humans, animals, and the environment”, began gaining momentum. This followed continually occurring, global, highly visible, zoonotic infectious disease outbreaks, that highlighted the links between an increasing human population, mixing of human and animal habitats, growing globalization, a changing climate, and recognition that a diverse expertise would be needed for early disease detection, and effective prevention and control.
One Health and Planetary Health share a set of underlying principles:
Given the immensity of the challenge we face, there is a compelling imperative to align One Health and Planetary Health forces. Why and how they are aligned, and challenges to overcome will be discussed.
Thirty years after the construction of the Diama Dam triggered an epidemic of Schistosoma mansoni and haematobium infections along the Senegal River and Lac de Guiers, this region remains an hyper-endemic area for human schistosomiasis with prevalence of infection in affected communities often exceeding 50%. The persistence of disease despite mass drug administration underlines the importance of the human-environment interactions that leave rural populations chronically exposed to reinfection through their daily economic, household and hygienic activities. The goal of this study was to estimate the body surface area exposed while performing seven different water contact activities common in the region. Brief interviews were conducted with residents in 5 villages along the lower basin of the Senegal River and 10 on the Lac de Guiers. For each water contact activity, adult male and female interviewees were asked to indicate the parts of the body that come into contact with water while performing that activity. Answers were registered on a diagram used to measure burn size, from which percent body surface area exposed could be calculated. Activity-specific body surface exposure data were complemented by published data on the time-demands of each activity in the northern Senegalese context. Time and body surface area data were then combined to compute an activity-based exposure metric. Our analysis showed that there is some community-level variability in the nature of water contact, mostly driven by environmental characteristics of water points, type of irrigation infrastructure and fishing practices. Anyway, commonalities in water contact behavior across communities were more pronounced than differences. We thus argue that an exposure metric derived from known time and body surface area demands of different activities could be usefully employed to better understand the schistosomiasis risk as a function of the types of water contact activities performed by different members of the population.
Climate change may alter the spread of directly transmitted infections as climatological factors such as relative humidity and temperature affect the suspension of disease-carrying droplets. This impact remains relatively understudied for many directly-transmitted infections. Using a unique long-term dataset from Mexico, in conjunction with statistical and analytical tools from both infectious disease biology and climatology, we test for associations between climatic conditions and incidence of three common childhood infections. We find that drier conditions (lower humidity) increases the transmission of the varicella virus after controlling for seasonality and long term changes in incidence, which is consistent with previous findings for influenza. Temperature is not found to have a significant effect on transmission. In ongoing work we are testing these associations for scarlet fever and RSV.
The second contribution of this paper is to synthesize alternate methods for estimating climate-transmission relationships. We estimate the unobserved transmission rates from the incidence data using a mechanistic disease transmission model. We combine these estimates with panel regression methods to estimate the effect of environmental variables on transmission, allowing construction of projection models. Finally, we formally evaluate our ability to detect an effect of climate change from incidence data using simulations to reflect increasing degrees of stochasticity and underreporting across a broad range of driving relationships between climate and transmission.
The past two decades have witnessed an unprecedented evolution in human development, yet there remain persistent gaps in the coverage of a wide variety of essential health services, what is known as the Global Health Delivery Gap. Meanwhile, the health of the earth’s natural systems continue to deteriorate along with our endowments of natural capital. There are two common challenges between the Global Health and the Planetary Health movements that are poorly resolved: 1) creating practical systems-level change at the ground level, and 2) establishing metrics and evaluation to measure that change and produce transferable knowledge for scaling or replication.
Through a partnership between a conservation (Centre ValBio) and healthcare (PIVOT) organization, the Madagascar government, and academic partners, we have established a new initiative that combines evidence-based health system strengthening with ecological restoration to develop a model system for Global and Planetary Health in Ranomafana Madagascar (a UN World Heritage Site). Central to this is a new data platform for information systems and research that include: 1) health management information systems (HMIS); 2) environmental disease surveillance, and 3) geo-coded prospective longitudinal cohort study of health and economic conditions of over 1500 households (~7000 individuals) with a true baseline. The data platform allows for inferring relative effects of health system and environmental change on population health such as mortality rates. It provides a powerful foundation for integrating health systems research with basic science and innovation in a new era of Planetary Health.