Boletim mensal VigiAR: 02/2024: volume 66

O Programa em Saúde Ambiental relacionado a populações expostas à poluição do ar do Município de São Paulo (VIGIAR) tem por objetivo desenvolver ações de vigilância em saúde ambiental, para populações expostas aos poluentes atmosféricos, de forma a orientar medidas de prevenção, promoção da saúde e de atenção integral, conforme preconizado pelo Sistema Único de Saúde (SUS).

A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia.

The mosquito-borne dengue virus remains a major public health concern in Malaysia. Despite various control efforts and measures introduced by the Malaysian Government to combat dengue, the increasing trend of dengue cases persists and shows no sign of decreasing. Currently, early detection and vector control are the main methods employed to curb dengue outbreaks. In this study, a coupled model consisting of the statistical ARIMAX model and the deterministic SI-SIR model was developed and validated using the weekly reported dengue data from year 2014 to 2019 for Selangor, Malaysia. Previous studies have shown that climate variables, especially temperature, humidity, and precipitation, were able to influence dengue incidence and transmission dynamics through their effect on the vector. In this coupled model, climate is linked to dengue disease through mosquito biting rate, allowing real-time forecast of dengue cases using climate variables, namely temperature, rainfall and humidity. For the period chosen for model validation, the coupled model can forecast 1-2 weeks in advance with an average error of less than 6%, three weeks in advance with an average error of 7.06% and four weeks in advance with an average error of 8.01%. Further model simulation analysis suggests that the coupled model generally provides better forecast than the stand-alone ARIMAX model, especially at the onset of the outbreak. Moreover, the coupled model is more robust in the sense that it can be further adapted for investigating the effectiveness of various dengue mitigation measures subject to the changing climate.

A meta-analysis on global change drivers and the risk of infectious disease.

Anthropogenic change is contributing to the rise in emerging infectious diseases, which are significantly correlated with socioeconomic, environmental and ecological factors1. Studies have shown that infectious disease risk is modified by changes to biodiversity2-6, climate change7-11, chemical pollution12-14, landscape transformations15-20 and species introductions21. However, it remains unclear which global change drivers most increase disease and under what contexts. Here we amassed a dataset from the literature that contains 2,938 observations of infectious disease responses to global change drivers across 1,497 host-parasite combinations, including plant, animal and human hosts. We found that biodiversity loss, chemical pollution, climate change and introduced species are associated with increases in disease-related end points or harm, whereas urbanization is associated with decreases in disease end points. Natural biodiversity gradients, deforestation and forest fragmentation are comparatively unimportant or idiosyncratic as drivers of disease. Overall, these results are consistent across human and non-human diseases. Nevertheless, context-dependent effects of the global change drivers on disease were found to be common. The findings uncovered by this meta-analysis should help target disease management and surveillance efforts towards global change drivers that increase disease. Specifically, reducing greenhouse gas emissions, managing ecosystem health, and preventing biological invasions and biodiversity loss could help to reduce the burden of plant, animal and human diseases, especially when coupled with improvements to social and economic determinants of health.

Think tanks and climate obstruction: Atlas affiliates in Canada.

This paper provides a longitudinal social network and content analysis of Canadian think tanks affiliated with the Atlas network, analyzing their efforts to obstruct climate action over the last two decades. Network analysis reveals extensive and deepening board interlocks and joint memberships between these think tanks and the fossil fuel industry, other policy-planning organizations within and beyond Canada, and academic institutions. Consistent with and rooted in network ties, Atlas members produce a large and growing volume of climate-related content, including content that denies the reality and impacts of climate change, promotes and defends the fossil fuel sector, and opposes climate policy and action. Atlas affiliates are argued to be at the core of a reactionary segment of Canada's elite policy-planning network opposed to virtually all forms of climate action, while the frames and campaigns they deploy are seen as a force obstructing progress on climate change.

Cet article propose une analyse longitudinale des réseaux sociaux et du contenu des groupes de réflexion canadiens affiliés au réseau Atlas, en analysant leurs efforts d'obstruction à l'action climatique au cours des deux dernières décennies. L'analyse des réseaux révèle des liens étendus et de plus en plus profonds entre les conseils d'administration et les membres conjoints de ces groupes de réflexion et l'industrie des combustibles fossiles, d'autres organisations de planification politique au Canada et à l'étranger, ainsi que des institutions universitaires. En accord avec les liens du réseau et enracinés dans ceux­ci, les membres de l'Atlas produisent un volume important et croissant de contenus liés au climat, y compris des contenus qui nient la réalité et les impacts du changement climatique, promeuvent et défendent le secteur des combustibles fossiles et s'opposent aux politiques et actions climatiques. Les affiliés d'Atlas sont considérés comme étant au cœur d'un segment réactionnaire du réseau d'élite de planification politique du Canada opposé à pratiquement toutes les formes d'action climatique, tandis que les cadres et les campagnes qu'ils déploient sont perçus comme une force qui entrave les progrès en matière de changement climatique.

Fertilizer management for global ammonia emission reduction.

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1-5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr-1, lower than previous estimates that did not fully consider fertilizer management practices6-9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr-1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases.

Unequal climate impacts on global values of natural capital.

Ecosystems generate a wide range of benefits for humans, including some market goods as well as other benefits that are not directly reflected in market activity1. Climate change will alter the distribution of ecosystems around the world and change the flow of these benefits2,3. However, the specific implications of ecosystem changes for human welfare remain unclear, as they depend on the nature of these changes, the value of the affected benefits and the extent to which communities rely on natural systems for their well-being4. Here we estimate country-level changes in economic production and the value of non-market ecosystem benefits resulting from climate-change-induced shifts in terrestrial vegetation cover, as projected by dynamic global vegetation models (DGVMs) driven by general circulation climate models. Our results show that the annual population-weighted mean global flow of non-market ecosystem benefits valued in the wealth accounts of the World Bank will be reduced by 9.2% in 2100 under the Shared Socioeconomic Pathway SSP2-6.0 with respect to the baseline no climate change scenario and that the global population-weighted average change in gross domestic product (GDP) by 2100 is -1.3% of the baseline GDP. Because lower-income countries are more reliant on natural capital, these GDP effects are regressive. Approximately 90% of these damages are borne by the poorest 50% of countries and regions, whereas the wealthiest 10% experience only 2% of these losses.