There is increasing evidence that climate change impacts have been particularly critical in the case of heat waves during the last years. Many cities around the globe have been affected by heat waves and their cascading effects, threatening public health and urban life and disrupting services and infrastructure. Unfortunately, cities in developing countries are not paying attention to heatwaves’ impacts. This is the case in Mexico. Although there are studies on extreme heat exposure, there are no vulnerability assessments. The central research question of our study is the analysis of social vulnerability to extreme temperature and heatwaves in two Mexican cities at the U.S.-Mexico border, Tijuana, and Mexicali. Our results show that urban planning and state and municipal development policies in both cities have neglected the impact of heat waves despite their increasing frequency, intensity, and duration in the last two decades. The results also show significant differences in exposure, sensitivity, and adaptive capacity to extreme temperatures within each city. Areas with higher vulnerability in both cities are informal settlements and low-income neighborhoods. This information can support local governments in making sound use of scarce resources to create efficient responses to current impacts and future risks of climate change.
Chagas disease, considered a neglected disease, was initially confined to rural localities in endemic areas; however, in recent years through the process of urbanization and migration of infected people, the disease is gaining importance in urban environments. The presence of the vector in urban areas in most cases is due to the passive transport of vectors, but recently, its presence seems to be linked to vector adaptation processes associated with climate change. This paper reports the occurrence of an infected triatomine in the peridomicile of a house in an urban area of Córdoba, Veracruz, Mexico, where the species found is described, the molecular characteristics and resistance to BZN and NFX of the Trypanosoma cruzi isolate obtained, as well as serological data of the dwelling inhabitants. These urban disease scenarios make it possible to generate new scientific knowledge and enable the creation of new control strategies for Chagas disease vectors.
Anthropogenic and natural disasters (e.g., wildfires, oil spills, mine spills, sewage treatment facilities) cause water quality disturbances in fluvial networks. These disturbances are highly unpredictable in space-time, with the potential to propagate through multiple stream orders and impact human and environmental health over days to years. Due to challenges in monitoring and studying these events, we need methods to strategize the deployment of rapid response research teams on demand. Rapid response research has the potential to close the gap in available water quality data and process understanding through time-sensitive data collection efforts. This manuscript presents a protocol that can guide researchers in preparing for and researching water quality disturbance events. We tested and refined the protocol by assessing the longitudinal propagation of water quality disturbances from the 2022 Hermit’s Peak-Calf Canyon, NM, USA, the largest in the state’s recorded history. Our rapid response research allowed us to collect high-resolution water quality data with semi-continuous sensors and synoptic grab sampling. The data collected have been used for traditional peer-reviewed publications and pragmatically to inform water utilities, restoration, and outreach programs.
Young people today are predicted to experience more climate change related stressors and harms than the previous generation, yet they are often excluded from climate research, policy, and advocacy. Increasingly, this exposure is associated with experience of common mental health disorders (CMD). The VoCes-19 study collected surveys from 168,407 young people across Mexico (ages 15-24 years) through an innovative online platform, collecting information on various characteristics including CMD and experience of recent climate harms. Logistic regression models were fit to explore characteristics associated with CMD. Structural equation models were fit to explore pathways between exposure, feeling of concern about climate change, and a sense of agency (meaning the respondent felt they could help address the climate crisis) and how these relate to CMD. Of the respondents, 42% (n = 50,682) were categorized as experiencing CMD, higher among those who experienced a climate stressor (51%, n = 4,808) vs those not experiencing climate stressors (41%, n = 43,872). Adjusting for key demographic characteristics, exposure to any climate event increased the odds of CMD by 50% (Odd Ratio = 1.57; 95% Confidence Interval (CI) 1.49, 1.64), highest for heatwaves. Specific climate impacts such as housing damage, loss of or inability to work, damage to family business, leaving school and physical health affected were adversely related to CMD, though for different climate hazards. More concern and less agency were related to CMD through different pathways, particularly for those exposed to recent events. Future research regarding the cumulative exposures to climate change, not just acute events but as an ongoing crisis, and various pathways that influence the mental health and well-being of young people must be clearly understood to develop programs and policies to protect the next generation.
Despite being perceived as a warm country, winters in the Central Mexican Plateau frequently reach temperatures below zero Celsius. Prolonged exposures to low temperatures resulting in heart and respiratory morbidities are estimated to be responsible for 50% of the reported illness in the plateau, attributable primarily to the design of homes ill-suited to extreme temperatures. Consequently, there is a growing need to ensure that dwellings provide adequate indoor thermal conditions in the region. Hence, on-site sensors were used to collect temperature and relative humidity data every five minutes in 26 living rooms in the Plateau for 11 months. From these data, a subsample was determined, resulting in dwelling-level thermal comfort and health surveys on 15 homes. Computer simulations were used to investigate whether the building itself could provide thermal comfort under different retrofitting scenarios. Multiple linear regression relating the Predicted Percentage Dissatisfaction (PPD) index to self-perceived health was undertaken. Both monitored and simulated results were matched against our underheating model, finding that 92% of the homes had cold indoor environments, some even during summer. High PPD and intense levels of underheating were positive predictors of higher self-reported health problems. More self-reported health problems were correlated with both lower life satisfaction and self-worth, and with subjects’ use of more adaptive strategies against environmental dissatisfaction. Dynamic computer simulations suggested that indoor thermal environments could be improved by enforcing the non-utilised standard NOM-ENER-020, which recommends the addition of insulation on walls and roofs. These findings suggest that the cold environments within homes of the plateau influence the self-perceived physical and mental health of its population. Hence, the application of adequate measures, such as retrofitting homes with stronger standards than the existing NOM-ENER-020 are needed in place.
One of the climate problems that causes the most environmental impact worldwide is the trend of increasing occurrence of events of maximum extreme temperature, signaled by indicators such as hot extremes (HE) and maximum maximorum (highest maximum) temperature (MmT). These events can cause conditions ranging from severe droughts to heat stroke, which can cause death in any population. Indicators of maximum extreme temperature in one of the most important agricultural areas in northwestern Mexico were calculated based on significant trends (ST) and adjusted return periods. To calculate the trends of the maximum extreme tempera-ture, frequency (FR), annual average duration (AAD), annual daily duration (ADD), intensity (IN) of HE, and MmT, the Mann-Kendall and Sen’s slope tests were applied to data obtained for 19 weather stations from the CLImate COMputing database for the period 1982-2014. Adjusted return periods (ARP) were calculated for each indicator of maximum extreme temperature by fitting a probability distribution function. For the study area, the ST and maximum extreme temperature shows a prevailing cooling trend. This can be deduced by observing the proportion of negative ST compared with positive ST. The highest positive magnitudes of ST were recorded at stations CUL (FR = 3.44 HE dec-1), GUT (AAD = 6.15 day HE-1 dec-1and IN = 13.62 degrees C dec-1), IXP (ADD = 35.00 day dec-1) and POT (MmT = 2.50 degrees C day-1 dec-1). For ARP, the estimate of the average occurrence frequency of extreme events per100 years are FR = 6.11 HE dec-1 (1 time), AAD = 6.64 day HE-1 dec-1 (4 times), ADD = 38.68 day dec-1 (1 time), IN = 39.09 degrees C dec-1 (6 times) and MmT = 41.95 degrees C day-1 dec-1 (1 time). These findings are of key importance for the economic sectors related to agricultural production in the state known, at least to date, as “the breadbasket of Mexico” (Sinaloa). The results will help to develop adaptation/prevention measures before the coming socioeconomic and hydrological disasters.
In recent years, the morbidity and mortality rates caused by stings and bites of poisonous species have been constant in Mexico; such a phenomenon has been emphasized due to the dominance or modification of the natural geosystem. The modification in the availability of water resources has caused changes in the climate, extreme droughts, and floods that influence the distribution of species, generating risks where they did not occur before. With the aforementioned, it is important to identify risky points through the development of new cartography in the country, which allows an analysis from a spatial and geostatistical perspective. Based on the number of victims of stings or bites, there will be a sharp increase in exposure to poisonous animals where the distribution of these species overlaps with areas of high vulnerability as well as social and natural contact in Mexico. The aim of this study is to model the anthropogenic risk of poisonous species in Mexico in a spatial way (data from 2010-2017). The spatial analyses of this study were carried out throughout the Mexican territory and focused on species such as coral snakes, rattlesnakes, scorpions, and centipedes. The variables of vulnerability, danger, and exposure were considered to create a generalized risk model using the core area alternative in the zonation program, allowing a spatial analysis. The methodology consisted of six stages: (1) the identification of threats and records collected from chosen poisonous animals; (2) obtaining risk models by using the Zonation software that summarized all the species distribution modeling (SDM); (3) the development of a general anthropogenic vulnerability indicator; (4) obtaining the general exposure model with the index of accessibility to medical services; (5) obtaining risk models; and (6) the validation of risk models with morbidity and mortality rates by obtaining geostatistical models. The highlighted risk areas are the Pacific Ocean coast from Southern Sinaloa to the border of Michoacan, a corridor from central Veracruz to northern Oaxaca, central Guerrero, northern Michoacan, and northwestern Nuevo Leon.
Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus (DENV) serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling. We fit climatic variables to municipality presence records from 2012 to 2020 in Mexico. Bioclimatic variables were explored for their environmental suitability to different DENV serotypes, and the different distributions were visualized using three cutoff probabilities representing 90%, 95%, and 99% sensitivity. Municipality-level results were then mapped in ArcGIS. The overall accuracy for the predictive models was 0.69, 0.68, 0.75, and 0.72 for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Important predictors of all DENV serotypes were the growing degree days for December, January, and February, which are an indicator of higher temperatures and the precipitation of the wettest month. The minimum temperature of the coldest month between -5 & DEG;C and 20 & DEG;C was found to be suitable for DENV-1 and DENV-2 serotypes. Respectively, above 700-900 mm of rainfall, the suitability for DENV-1 and DENV-2 begins to decline, while higher humidity still favors DENV-3 and DENV-4. The sensitivity concerning the suitability map was developed for Mexico. DENV-1, DENV-2, DENV-3, and DENV-4 serotypes will be found more commonly in the municipalities classified as suitable based on their respective sensitivity of 91%, 90%, 89%, and 85% in Mexico. As the microclimates continue to change, specific bioclimatic indices may be used to monitor potential changes in DENV serotype distribution. The suitability for DENV-1 and DENV-2 is expected to increase in areas with lower minimum temperature ranges, while DENV-3 and DENV-4 will likely increase in areas that experience higher humidity. Ongoing surveillance of municipalities with predicted suitability of 89% and 85% should be expanded to account for the accurate DENV serotype prevalence and association between bioclimatic parameters.
In this article we connect theoretically the concepts of structural vulnerabilities, recursive crises, and disasters through the linking-up of the COVID-19 pandemic with extreme hydrometeorological events in three municipalities in southern Yucatan, Mexico. The main research goal was to show the effects in productive and commercial systems in beekeeper and farmer households and their coping strategies to highlight the inter-relationships between historical vulnerabilities, crises, and disasters. The methodological approach included ethnographic fieldwork, 101 semi-structured interviews, and five focal groups. In the results, we reconstruct the agro-productive and commercial vulnerabilities built up since 1960 and contextualize the health and hydrometeorological crisis to show how some 87% of households suffered severe consequences to their incomes. The prices of main products (maize, fruit, honey) reached historically low levels as a result of conditions within local markets during the crisis. Half of the households surveyed had to make use of savings and more than 60% received no support from government or from development agencies. We conclude by pointing out the need for accompanying the design and implementation of community mitigation plans, which should take as a starting point the recovery of knowledge and local organization in order to demand from government co-managed, preventive programs, and capacities that would enable communities to confront increasing negative consequences in situations of global climate change and market instabilities in local peasant contexts. Our study aims to reach policy-makers, social organizations, and communities in order to highlight the importance of developing joint capabilities to respond to growing environmental, economic, and health vulnerabilities.
The Getis-Ord G(i)* statistic clustering technique was used to create a hot spot exposure map using 14 potentially toxic elements (PTEs) found in urban dust samples in a semiarid city in northwest Mexico. The dust distribution and deposition in this city are influenced by the seasonal wind and rain from the North American Monsoon. The spatial clustering patterns of hot spots were used in combination with a sensitivity analysis to determine which variables most influenced the PTE hot spot exposure base map. The hot spots areas (%) were used as indicators of environmental vulnerability, and a final integrated map was selected to represent the highest vulnerability of PTEs with a 99% level of confidence. The results of the sensitivity analysis indicated that the flood zones and pervious and impervious zones were the most sensitive variables due to their weight in the spatial distribution. The hot spot areas were reduced by 60.4% by not considering these variables. The hot spot analysis resulted in an effective tool that allowed the combination of different spatial layers with specific characteristics to determine areas that present greater vulnerability to the distribution of PTEs, with impacts on public and environmental health.
Chagas disease, caused by the protozoa Trypanosoma cruzi, is an important yet neglected disease that represents a severe public health problem in the Americas. Although the alteration of natural habitats and climate change can favor the establishment of new transmission cycles for T. cruzi, the compound effect of human-modified landscapes and current climate change on the transmission dynamics of T. cruzi has until now received little attention. A better understanding of the relationship between these factors and T. cruzi presence is an important step towards finding ways to mitigate the future impact of this disease on human communities. Here, we assess how wild and domestic cycles of T. cruzi transmission are related to human-modified landscapes and climate conditions (LUCC-CC). Using a Bayesian datamining framework, we measured the correlations among the presence of T. cruzi transmission cycles (sylvatic, rural, and urban) and historical land use, land cover, and climate for the period 1985 to 2012. We then estimated the potential range changes of T. cruzi transmission cycles under future land-use and -cover change and climate change scenarios for 2050 and 2070 time-horizons, with respect to “green” (RCP 2.6), “business-as-usual” (RCP 4.5), and “worst-case” (RCP 8.5) scenarios, and four general circulation models. Our results show how sylvatic and domestic transmission cycles could have historically interacted through the potential exchange of wild triatomines (insect vectors of T. cruzi) and mammals carrying T. cruzi, due to the proximity of human settlements (urban and rural) to natural habitats. However, T. cruzi transmission cycles in recent times (i.e., 2011) have undergone a domiciliation process where several triatomines have colonized and adapted to human dwellings and domestic species (e.g., dogs and cats) that can be the main blood sources for these triatomines. Accordingly, Chagas disease could become an emerging health problem in urban areas. Projecting potential future range shifts of T. cruzi transmission cycles under LUCC-CC scenarios we found for RCP 2.6 no expansion of favourable conditions for the presence of T. cruzi transmission cycles. However, for RCP 4.5 and 8.5, a significant range expansion of T. cruzi could be expected. We conclude that if sustainable goals are reached by appropriate changes in socio-economic and development policies we can expect no increase in suitable habitats for T. cruzi transmission cycles.
BACKGROUND: The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV) clusters in Mexico. METHODS: We present an integrated analysis of Aedes-borne diseases (ABDs), the local climate, and the socio-demographic profiles of 2469 municipalities in Mexico. We used SaTScan to detect spatial clusters and utilize the Pearson correlation coefficient, Randomized Dependence Coefficient, and SHapley Additive exPlanations to analyze the influence of socio-demographic and climatic factors on the prevalence of ABDs. We also compare six machine learning techniques, including XGBoost, decision tree, Support Vector Machine with Radial Basis Function kernel, K nearest neighbors, random forest, and neural network to predict risk factors of ABDs clusters. RESULTS: DENV is the most prevalent of the three diseases throughout Mexico, with nearly 60.6% of the municipalities reported having DENV cases. For some spatiotemporal clusters, the influence of socio-economic attributes is larger than the influence of climate attributes for predicting the prevalence of ABDs. XGBoost performs the best in terms of precision-measure for ABDs prevalence. CONCLUSIONS: Both socio-demographic and climatic factors influence ABDs transmission in different regions of Mexico. Future studies should build predictive models supporting early warning systems to anticipate the time and location of ABDs outbreaks and determine the stand-alone influence of individual risk factors and establish causal mechanisms.
Dipetalogaster maxima is a primary vector of Chagas disease in the Cape region of Baja California Sur, Mexico. The geographic distribution of D. maxima is limited to this small region of the Baja California Peninsula in Mexico. Our study aimed to construct the ecological niche models (ENMs) of this understudied vector species and the parasite responsible for Chagas disease (Trypanosoma cruzi). We modelled the ecological niches of both species under current and future climate change projections in 2050 using four Representative Concentration Pathways (RCPs): RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5. We also assessed the human population at risk of exposure to D. maxima bites, the hypothesis of ecological niche equivalency and similarity between D. maxima and T. cruzi, and finally the abundance centroid hypothesis. The ENM predicted a higher overlap between both species in the Western and Southern coastal regions of the Baja California Peninsula. The climate change scenarios predicted a Northern shift in the ecological niche of both species. Our findings suggested that the highly tourist destination of Los Cabos is a high-risk zone for Chagas disease circulation. Overall, the study provides valuable data to vector surveillance and control programs.
Air pollution is one of the most challenging global sustainability problems in the world. Roughly 90% of global citizens live in areas that exceed the acceptable air pollution levels according to the World Health Organization air quality guidelines. However, socially disadvantaged groups are disproportionately located in areas exposed to higher levels of air pollution. Understanding the association between risk exposure to air pollutants and the underlying socio-economic factors determining risk is central for sustainable urban planning. The purpose of this study was to explore environmental inequalities in Mexico City, specifically the spatial association between air pollutants and socioeconomic status (SES) indicators. We propose that SES indicators will be expected to spatially cluster vulnerable individuals and groups into heavily polluted areas. To test this hypothesis, we used 2017-2019 data from governmental records to perform spatial interpolations to explore the spatial distribution of criteria pollutants. We carried out spatial autocorrelations of air pollutants and SES indicators using the bivariate Moran’s I index. Our findings provide strong evidence of spatial heterogeneity in air pollution exposure in Mexico City. We found that socially deprived areas located in the southern periphery of Mexico City were exposed to higher ozone concentrations. On the contrary, wealthiest areas concentrated in the city center were exposed to greater concentrations of nitrogen dioxide and carbon monoxide. Our findings highlight the need for policy-driven approaches that take into consideration not only the geographic variability and meteorological dynamics associated with air pollution exposure, but also the management of socioeconomic risk factors aimed at reducing disparate exposure to air pollution and potential health impacts.
The urban heat island (UHI) is mostly due to urbanization. This phenomenon in concert with the high temperatures caused by global climate change may profoundly affect human thermal comfort, which can influence human productivity and morbidity especially in spring/summer period. The main objective of this investigation was to determine changes in degree of thermal comfort of Mexico City’s inhabitants and compare it with the physiological equivalent temperature (PET) to evaluate whether PET and its categorization are adequate to be applied in Mexico City. A series of microclimatological measurements to estimate PET were made at four sites including the city’s center. Concomitantly, a series of surveys of thermal perception were applied to 1300 passersby. The results show that PET has increased from 1990 to 2020 from 0.1208 degrees C/year to 0.1498 degrees C/year in the study sites, in addition to overestimating the degree of thermal comfort of people according to the stablished categories or classes. It is concluded that it is necessary to adjust thermal stress categories. Knowing the percentages of people without thermal comfort will lead us to determine different ranges in environmental parameters to define an acceptable environment for most people.
Intracranial aneurysms are considered acquired lesions, occur with an incidence of 3-5% in general population. Subarachnoid hemorrhage (SAH) due to ruptured aneurysms represents 85 of all spontaneous subarachnoid hemorrhages and this represents 15% of all cerebral vascular events. Risk factors for aneurysmal rupture are age, gender, size and location of the aneurysm, hypertension, smoking, and alcoholism. Whether seasonal or meteorological factors influence the likelihood of aneurysm rupture is controversial. An observational, retrospective, cross-sectional and non-comparative study of male and female patients over 18 years old who were admitted to our unit in northeast Mexico with the diagnosis of spontaneous SAH due to aneurysmal rupture from January 2014 to March 2020. Climate information was obtained from data of the climate history of the different airport stations in the northeast of the country and the information was correlated to determine if meteorological variables interfere in the incidence of SAH due to aneurysm rupture. Our study showed a significant seasonal fluctuation on the occurrence of aneurysmal SAH. A statistically significant relationship between temperature, humidity and aneurismal SAH. The atmospheric pressure did not show a statistically significant relationship with SAH incidence due to aneurysm rupture.
The supply of drinking water to the population is an important challenge facing humanity, since both surface and underground sources present a great variability of water storage with respect to space and time. This problem is further aggravated in arid and semi-arid areas where rainfall is low and torrential, which makes groundwater the main source of supply; therefore, it is necessary to carry out studies that allow evaluating the evolution of the quantity and quality of water. This study addresses the behavior of groundwater in a semi-arid region, considering the theory of flow systems to identify movement as well as water quality, es determined by a water quality index (WQI), calculated considering arsenic and fluorine. In addition, a quality irrigation classification is used, employing the norms in accordance with international standards and the Mexican Norm, which allows for a comparison. Local, regional, intermediate and mixed flow systems are identified, and the evolution of cations and anions in addition to temperature is examined. It is observed that the drinking water quality index classifies them as excellent in most of the monitored wells (<50), but with a negative evolution. Regarding irrigation, most of the water samples are classified without restriction for the establishment of any type II crop (C(2)S(1)) and with restrictions for horticultural crops. It is observed that arsenic had values between 0.49 and 61.40 (µg/L) in 2005, while in 2015 they were between 0.10 and 241.30 (µg/L). In addition, fluoride presented values between 0.00 and 2.6 (mg/L) in 2005, while in 2015 they were between 0.28 and 5.40 (mg/L). The correlations between arsenic and fluorine are noted as well as WQI and SAR. A finding in this research was to include arsenic and fluorine in the calculation of the WQI allowing a better interpretation of the quality of water for both human consumption and for agricultural use to based on this make the best decision to control any harmful effects for the population, in addition to identifying the appropriate purification treatment required to control pollutants. It is concluded that arsenic is an element of utmost importance when considering water quality, so it is necessary to examine its evolution and continue to monitor its levels constantly.
Climate change adaptation is an increasingly important topic addressed in the face of the current and expected future impacts by climate change that the social, economic and ecological systems are experiencing worldwide. Despite the advances reported in the literature, adaptation to climate change is still considered a challenge to move from planning to the practical implementation of successful interventions. In this regard, identifying international key barriers, exchanges of experiences and lessons learned may facilitate the progress of the coasts’ sustainable and resilient future. The coast of Mexico is an excellent study area. High population densities occur along the coastal zone, whose main economic activity is related to primary and tertiary sectors. Additionally, a great diversity of coastal ecosystems exists, which are threatened by anthropogenic and hydrometeorological impacts. Under these circumstances, the population is becoming aware of the urgent need to adapt to the consequences of climate change. In this sense, this paper reviews research contributions concerning population perception to climate change and adaptation strategies in Mexico’s coastal zone. The findings highlight critical institutional difficulties and social barriers that have impeded the effective implementation of adaptation strategies to climate change in Mexico and consider steps to address them. However, adaptation strategies that show the prevention culture of some coastal communities have been found and also results of successful projects carried out, especially on mangrove forest and coral reef restoration, which are of essential importance to consider to progress on the path of a successful adaptation to climate change in Mexico.
Rising global temperatures and seawater temperatures have led to an increase in extreme weather patterns leading to droughts and floods. These natural phenomena, in turn, affect the supply of drinking water in some communities, which causes an increase in the prevalence of diseases related to the supply of drinking water. The objective of this work is to demonstrate the effects of global warming on human health in the population of Monterrey, Mexico after Hurricane Alex. We interpolated data using statistical downscaling of climate projection data for 2050 and 2080 and correlated it with disease occurrence. We found a remarkable rise in the incidence of transmissible infectious disease symptoms. Gastrointestinal symptoms predominated and were associated with drinking of contaminated water like tap water or water from communal mobile water tanks, probably because of the contamination of clean water, the disruption of water sanitation, and the inability to maintain home hygiene practices.
We examine the impact of temperature on mortality in Mexico using daily data over the period 1998-2017 and find that 3.8 percent of deaths in Mexico are caused by suboptimal temperature (26,000 every year). However, 92 percent of weather-related deaths are induced by cold (<12 degrees C) or mildly cold (12-20 degrees C) days and only 2 percent by outstandingly hot days (>32 degrees C). Furthermore, temperatures are twice as likely to kill people in the bottom half of the income distribution. Finally, we show causal evidence that the Seguro Popular, a universal health care policy, has saved at least 1,600 lives per year from cold weather since 2004.
BACKGROUND: Climate variability influences the population dynamics of the Aedes aegypti mosquito that transmits the viruses that cause dengue, chikungunya and Zika. In recent years these diseases have grown considerably. Dengue is now the fastest-growing mosquito-transmitted disease worldwide, putting 40 per cent of the global population at risk. With no effective antiviral treatments or vaccines widely available, controlling mosquito population remains one of the most effective ways to prevent epidemics. This paper analyses the temporal and spatial dynamics of dengue in Mexico during 2000-2020 and that of chikungunya and Zika since they first appeared in the country in 2014 and 2015, respectively. This study aims to evaluate how seasonal climatological variability affects the potential risk of transmission of these mosquito-borne diseases. Mexico is among the world’s most endemic countries in terms of dengue. Given its high incidence of other mosquito-borne diseases and its size and wide range of climates, it is a good case study. METHODS: We estimate the recently proposed mosquito-borne viral suitability index P, which measures the transmission potential of mosquito-borne pathogens. This index mathematically models how humidity, temperature and precipitation affect the number of new infections generated by a single infected adult female mosquito in a host population. We estimate this suitability index across all Mexico, at small-area level, on a daily basis during 2000-2020. RESULTS: We find that the index P predicted risk transmission is strongly correlated with the areas and seasons with a high incidence of dengue within the country. This correlation is also high enough for chikungunya and Zika in Mexico. We also show the index P is sensitive to seasonal climatological variability, including extreme weather shocks. CONCLUSIONS: The paper shows the dynamics of dengue, chikungunya and Zika in Mexico are strongly associated with seasonal climatological variability and the index P. This potential risk of transmission index, therefore, is a valuable tool for surveillance for mosquito-borne diseases, particularly in settings with varied climates and limited entomological capacity.
Urban floods can be contaminated with fecal material and pathogens. Evidence on infection risks associated with exposure to waterborne pathogens in urban floods is lacking. We address this gap by assessing the risk of infection from exposure to Giardia lamblia in urban flood water samples in Mexico City using a QMRA. Historical flood data was used to build severity indices and to test for correlations with risk of infection estimates. Results indicate similar maximal pathogen densities in urban flood water samples to those from wastewater treatment plants. Significant positive correlations between risk of G. lamblia infection and severity indices suggest that floods could act as an important source of pathogen transmission in Mexico City. Risk of infection to G. lamblia is greater in the city’s periphery, which is characterized by high marginalization levels. We argue that these risks should be managed by engaging citizens, water, and health authorities in decision making.
Dengue is one of the major health problems in the state of Chiapas. Consequently, spatial information on the distribution of the disease can optimize directed control strategies. Therefore, this study aimed to develop and validate a simple Bayesian prediction spatial model for the state of Chiapas, Mexico. This is an ecological study that uses data from a range of sources. Dengue cases occurred from January to August 2019. The data analysis used the spatial correlation of dengue cases (DCs), which was calculated with the Moran index statistic, and a generalized linear spatial model (GLSM) within a Bayesian framework, which was considered to model the spatial distribution of DCs in the state of Chiapas. We selected the climatological, geographic, and sociodemographic variables related to the study area. A prediction of the model on Chiapas maps was carried out based on the places where the cases were registered. We find a spatial correlation of 0.115 (p value=0.001)between neighboring municipalities using the Moran index. The variables that have an effect on the number of confirmed cases of dengue are the maximum temperature (Coef=0.110; 95% CrI: 0.076 – 0.215), rainfall (Coef=0.013; 95% CrI:0.008 – 0.028), and altitude (Coef=0.00045; 95% CrI:0.00002 – 0.00174) of each municipality. The predicting power is notably better in regions that have a greater number of municipalities where DCs are registered. The model shows the importance of considering these variables to prevent future DCs in vulnerable areas.
ABSTRACT: Consumption of seeds has increased in recent years due to their high nutrient content. However, Salmonella outbreaks associated with the consumption of low-water-activity food items have also increased, although these food items do not support microbial growth. The main goal of this study was to quantify microbial indicators and to determine the prevalence and content of Salmonella in chia, amaranth, and sesame seeds obtained from Mexican retail outlets. In addition, the behavior of this pathogen on seeds was evaluated. One hundred samples of each product (chia, amaranth, and sesame seeds) were collected from Queretaro City markets. Aerobic plate count, coliforms, and Escherichia coli bacteria were quantified, and the presence and number of Salmonella pathogens were also determined. Chia, amaranth, and sesame seeds (1 kg each) were inoculated with a cocktail of five Salmonella strains (∼6 log CFU mL-1) and stored at ambient temperature, and then populations of Salmonella were quantified. The median aerobic plate count contents in chia, amaranth, and sesame seeds were 2.1, 2.4, and 3.8 log CFU g-1, respectively, and the content of coliforms on the seeds ranged from 0.48 to 0.56 log most probable number (MPN) per g. E. coli was present at low concentrations in the three types of seeds. Salmonella was detected in chia (31%), amaranth (15%), and sesame (12%) seeds, and the population ranged from 0.48 to 0.56 log MPN g-1. Salmonella levels decreased through 240 days of storage, showing inactivation rates of 0.017, 0.011, and 0.016 log CFU h-1 in chia, amaranth, and sesame seeds, respectively. The high prevalence of Salmonella in the seeds highlights potential risks for consumers, particularly given that seeds are generally consumed without treatments guaranteeing pathogen inactivation.
Currently, Salmonella spp. is the bacterium causing the highest number of food-borne diseases (FADs) in the world. It is primarily associated with contaminated water used to that irrigates crops from intensive livestock farming. However, literature emphasizes that the reservoirs for Salmonella spp. remain in wildlife and there are unconventional sources or secondary reservoirs, such as soil. Human soil-borne diseases have not been modeled in spatial scenarios, and therefore it is necessary to consider soil and other climatic factors to anticipate the emergence of new strains or serotypes with potential threat to public and animal health. The objective of this research was to investigate whether edaphic and climatic factors are associated with the occurrence and prevalence of Salmonella spp. in Northwestern Mexico. We estimated the potential distribution of Salmonella spp. with an interpolation method of unsampled kriging areas for 15 environmental variables, considering that these factors have a seasonal dynamic of change during the year and modifications in longer periods. Subsequently, a database was generated with human salmonellosis cases reported in the epidemiological bulletins of the National System of Epidemiological Surveillance (SIVE). For the Northwest region, there were 30,595 human cases of paratyphoid and other salmonellosis reported have been reported in Baja California state, 71,462 in Chihuahua, and 16,247 in Sonora from 2002 to 2019. The highest prevalence was identified in areas with higher temperatures between 35 and 37 °C, and precipitation greater than 1000 mm. The edaphic variables limited the prevalence and geographical distribution of Salmonella spp., because the region is characterized by presenting a low percentage of organic matter (≤4.3), and most of the territory is classified as aridic and xeric, which implies that the humidity comprises ≤ 180 days a year. Finally, the seasonal time series indicated that in the states of Baja California and Chihuahua the rainy quarter of the year is 18.7% and 17.01% above a typical quarter respectively, while for Sonora the warmest quarter is 23.3%. It is necessary to deepen the relationship between different soil characteristics and climate elements such as temperature and precipitation, which influence the distribution of different soil-transmitted diseases.
Environmental changes triggered by deforestation, urban expansion and climate change are present-day drivers of the emergence and reemergence of leishmaniasis. This review describes the current epidemiological scenario and the feasible influence of environmental changes on disease occurrence in the state of Yucatan, Mexico. Relevant literature was accessed through different databases, including PubMed, Scopus, Google, and Mexican official morbidity databases. Recent LCL autochthonous cases, potential vector sandflies and mammal hosts/reservoirs also have been reported in several localities of Yucatan without previous historical records of the disease. The impact of deforestation, urban expansion and projections on climate change have been documented. The current evidence of the relationships between the components of the transmission cycle, the disease occurrence, and the environmental changes on the leishmaniasis emergence in the state shows the need for strength and an update to the intervention and control strategies through a One Health perspective.
The negative synergistic effects of air pollution and sensible heat on public health have been noted in numerous studies. While separate, simplified, and public-facing indices have been developed to communicate the risks of unhealthful levels of air pollution and extreme heat, a combined index containing elements of both has rarely been investigated. Utilizing air quality, meteorology, and mortality data in Monterrey, Mexico, we investigated whether the association between the air quality index (AQI) and mortality was improved by considering elements of the heat index (HI). We created combined indices featuring additive, multiplicative, and either/or formulations and evaluated their relationship to mortality. Results showed increased associations with mortality for models employing indices that combined the AQI and the HI in an additive or multiplicative manner, with increases in the interquartile relative risk of 3-5% over that resulting from models employing the AQI alone.
Mexico is expected to become the 6th largest economy in 2050. According to EDGAR database, in 2019 it was the largest polluting country in Latin America and the 13th in the world, regarding Greenhouse Gas (GHG) emissions. Lately, the new Administration has shifted its energy strategy from a renewable path into the reinforcement of conventional energy sources. In this context, new policies have to be deployed to meet the Paris Agreement goals. In such scenario, carbon capture and storage (CCS) technology may contribute reducing CO2 emissions as a way to transform Mexico into a low-carbon economy in the long term. However, the construction and operation and maintenance phases will embody environmental impacts that should be considered. This paper assesses the carbon capture investments required for the expected increasing capacity of natural gas power plants up to 2050 and their impact on production, value added, employment, climate change, acidification, water consumption and human health effects. An environmentally extended multi-regional the input-output analysis (EMRIO) is used to address Mexican policies for the period 2020-2050. Results show that the investment in capture technologies in Mexico allows a net reduction of the carbon emissions in Mexico that is pursued at a low cost (33 EUR/tCO(2)). This mitigation policy has important additional co-benefits in terms of domestic value added and employment creation of medium and high qualification. As for the environmental impacts, most of them are produced in the power plant due to the burning of the natural gas consumed.
