The meteorological imbalances in Brazil have a strong impact on the lives of the population across the country, especially in the Amazon region. These impacts extend to meteorological phenomena, such as extreme rainfall, droughts, and an increase in temperature in several regions, as well as impacts on health, the economy, and, as the object of this study, the quality of life. This study presents the impact of meteorological changes on the quality of life in the Amazon region, based on (i) the thermal discomfort index (TDI), (ii) the temperature and humidity index (THI), and (iii) the effective temperature index as a function of the wind (TEFW). For this, meteorological data from the years 2003-2021 were used, in which the variables include total precipitation, global radiation, air-dry bulb temperature, the maximum temperature in the previous hour, the minimum temperature in the previous hour, relative humidity, and wind speed. This analysis indicates that for this tropical region, the sensation of mild discomfort was predominant in about 70% of the measurements, indicating a certain level of impact on the population’s quality of life, in addition to the fluctuation of levels of discomfort during periods of winter in that there are high rates of precipitation. The data control was performed with the removal of null data and calculation of monthly and annual averages, by using the compression (average) empty data frames in order to receive the values without losing the indexing of dates. At first, it was considered to use the kriging process to fill in the missing data; however, due to the existence of microclimates in the regions, the data could characterize remote regions in a generalized way, which would make it difficult to understand these data in comparison with the data from the National Institute of Meteorology (INMET, in Portuguese).
Thailand has made substantial progress towards malaria elimination, with 46 of the country’s 77 provinces declared malaria-free as part of the subnational verification program. Nonetheless, these areas remain vulnerable to the reintroduction of malaria parasites and the reestablishment of indigenous transmission. As such, prevention of reestablishment (POR) planning is of increasing concern to ensure timely response to increasing cases. A thorough understanding of both the risk of parasite importation and receptivity for transmission is essential for successful POR planning. Routine geolocated case- and foci-level epidemiological and case-level demographic data were extracted from Thailand’s national malaria information system for all active foci from October 2012 to September 2020. A spatial analysis examined environmental and climate factors associated with the remaining active foci. A logistic regression model collated surveillance data with remote sensing data to investigate associations with the probability of having reported an indigenous case within the previous year. Active foci are highly concentrated along international borders, particularly Thailand’s western border with Myanmar. Although there is heterogeneity in the habitats surrounding active foci, land covered by tropical forest and plantation was significantly higher for active foci than other foci. The regression results showed that tropical forest, plantations, forest disturbance, distance from international borders, historical foci classification, percentage of males, and percentage of short-term residents were associated with the high probability of reporting indigenous cases. These results confirm that Thailand’s emphasis on border areas and forest-going populations is well placed. The results suggest that environmental factors alone are not driving malaria transmission in Thailand; rather, other factors, including demographics and behaviors that intersect with exophagic vectors, may also be contributors. However, these factors are syndemic, so human activities in areas covered by tropical forests and plantations may result in malaria importation and, potentially, local transmission, in foci that had previously been cleared. These factors should be addressed in POR planning.
BACKGROUND: Weather fluctuation affects the incidence of malaria through a network of causuative pathays. Globally, human activities have ultered weather conditions over time, and consequently the number of malaria cases. This study aimed at determining the influence of humidity, temperature and rainfall on malaria incidence in an inland (Muyuka) and a coastal (Tiko) settings for a period of seven years (2011-2017) as well as predict the number of malaria cases two years after (2018 and 2019). METHODS: Malaria data for Muyuka Health District (MHD) and Tiko Health District (THD) were obtained from the Regional Delegation of Public Health and Tiko District Health service respectively. Climate data for MHD was obtained from the Regional Delegation of Transport while that of THD was gotten from Cameroon Development Coorporation. Spearman rank correlation was used to investigate the relationship between number of malaria cases and the weather variables and the simple seasonal model was used to forecast the number of malaria cases for 2018 and 2019. RESULTS: The mean monthly rainfall, temperature and relative humidity for MHD were 200.38 mm, 27.05(0)C, 82.35% and THD were 207.36 mm, 27.57 °C and 84.32% respectively, with a total number of malaria cases of 56,745 and 40,160. In MHD, mean yearly humidity strongly correlated negatively with number of malaria cases (r = - 0.811, p = 0.027) but in THD, a moderate negative yearly correlation was observed (r = - 0.595, p = 0.159). In THD, the mean seasonal temperature moderately correlated (r = 0.599, p = 0.024) positively with the number of malaria cases, whereas MHD had a very weak negative correlation (r = - 0.174, p = 0.551). Likewise mean seasonal rainfall in THD moderately correlated (r = - 0.559, p = 0.038) negatively with malaria cases, contrary to MHD which showed a very weak positive correlation (r = 0.425, p = 0.130). The simple seasonal model predicted 6,842 malaria cases in Muyuka, for 2018 and same number for 2019, while 3167 cases were observed in 2018 and 2848 in 2019. Also 6,738 cases of malaria were predicted for MHD in 2018 likewise 2019, but 7327 cases were observed in 2018 and 21,735 cases in 2019. CONCLUSION: Humidity is the principal climatic variable that negatively influences malaria cases in MHD, while higher seasonal temperatures and lower seasonal rain fall significantly increase malaria cases in THD.
Exposure to ambient temperature has been linked to adverse birth outcomes in several regions, including the USA, Australia, China, countries in the Middle East, and European countries. To date, no studies were performed in South America, a region with serious challenges related to climate change. Our investigation addresses this literature lack by examining the association between Low Birth Weight (LBW) and ambient temperature exposure in the largest county in South America, Brazil. We applied a nationwide case-control study design using a logistic regression model to estimate the odds ratio (OR) for LBW associated with ambient temperature during a specific trimester of pregnancy (1-3 trimester). Our sample size includes 5,790,713 birth records nationwide over 18 years (2001-2018), of which 264,967 infants were included in the model as cases of LBW, representing 4.6% of our total sample. We adjusted our model for several confounding variables, including weather factors, air pollution, seasonality, and SES variables at the individual level. Our findings indicate that North was the only region with positive and statistically significant associations in the primary analysis and most of the sensitivity analysis, which is the region where the Amazon is located. In this region, we estimated an increase of 5.16% (95%CI: 3.60; 6.74) in the odds of LBW per 1 °C increase in apparent temperature when the exposure occurred in the second trimester. Our results may be explained by the climate conditions in the Amazon region in the past years. A large body of literature indicates that the Amazon region has been facing serious climate challenges including issues related to policy, governance, and deforestation. Specifically, regarding deforestation, it is suggested that land use change and deforestation is projected to increase heat stress in the Amazon region, because of Amazon savannization, increasing the risk of heat stress exposure in Northern Brazil. Our study can assist public sectors and clinicians in mitigating the risk and vulnerability of the Amazonian population.
Reproductive seasonality is a phenomenon common to human and animal populations and driven by, among others, climatic variables. Given the currently changing climate and its impacts on both the environment and human lives, the question arises of its potential effects on reproductive seasonality. Few studies have specifically explored the seasonality of reproduction among hunter-gatherers and anyone investigated how current climate change might affect this phenomenon. In this study we addressed reproductive seasonality in the Baka Pygmy living in African rain forests. Since reproductive seasonality can be linked to weather patterns, we explore this possibility. However, climatic variables driving weather patterns have changed over the years, so we assessed whether this has influenced the Baka reproductive pattern. Based on 34 years of written birth records and oral questionnaires from 13 years of systematic fieldwork, we observed a bimodal birth pattern with two birth peaks at 6-month intervals. Our results demonstrate that precipitation at conception or at birth potentially has effects, respectively negative and positive on the monthly number of births; and temperature has a role in controlling other variables that do affect the reproductive pattern. Changing weather patterns appear to be affecting the reproductive seasonality in the Baka, suggesting that attention needs to be given to the influence of global climate change on forager societies.
