Exploring Dengue Dynamics: A Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia.

Our study examines how dengue fever incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales in the city of Ibagué, located in the Andean region of Colombia. We used the dengue incidence in Ibagué from 2013 to 2018 to examine the associations with climate, socioeconomic, and demographic factors from the national census and satellite imagery at four levels of local spatial aggregation. We used geographically weighted regression (GWR) to identify the relevant socioeconomic and demographic predictors, and we then integrated them with environmental variables into hierarchical models using integrated nested Laplace approximation (INLA) to analyze the spatio-temporal interactions.

The 2023 Latin America report of the Countdown on health and climate change: the imperative for health-centred climate-resilient development.

In 2023, a series of climatological and political events unfolded, partly driving forward the global climate and health agenda while simultaneously exposing important disparities and vulnerabilities to climate-related events. On the policy front, a significant step forward was marked by the inaugural Health Day at COP28, acknowledging the profound impacts of climate change on health. However, the first-ever Global Stocktake showed an important gap between the current progress and the targets outlined in the Paris Agreement, underscoring the urgent need for further and decisive action.

Ethical considerations related to drone use for environment and health research: A scoping review protocol.

Introduction: The use of drones in environment and health research is a relatively new phenomenon. A principal research activity drones are used for is environmental monitoring, which can raise concerns in local communities. Existing ethical guidance for researchers is often not specific to drone technology and practices vary between research settings.

A generalized framework for estimating snakebite underreporting using statistical models: A study in Colombia.

Background: Snakebite envenoming is a neglected tropical disease affecting deprived populations, and its burden is underestimated in some regions where patients prefer using traditional medicine, case reporting systems are deficient, or health systems are inaccessible to at-risk populations. Thus, the development of strategies to optimize disease management is a major challenge. We propose a framework that can be used to estimate total snakebite incidence at a fine political scale.

Bridging landscape ecology and urban science to respond to the rising threat of mosquito-borne diseases.

The prevalence of diseases borne by mosquitoes, particularly in the genus Aedes, is rising worldwide. This has been attributed, in part, to the dramatic rates of contemporary urbanization. While Aedes-borne disease risk varies within and between cities, few investigations use urban science-based approaches to examine how city structure and function contribute to vector or pathogen introduction and maintenance.

Estimating and forecasting the burden and spread of Colombia's SARS-CoV2 first wave.

Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale non-pharmaceutical interventions (NPIs) were implemented as national emergencies in most of the country's municipalities, starting with a lockdown on March 20th, 2020. Recently, approaches that combine movement data (measured as the number of commuters between units), metapopulation models to describe disease dynamics subdividing the population into Susceptible-Exposed-Asymptomatic-Infected-Recovered-Diseased and statistical inference algorithms have been pointed as a practical approach to both nowcast and forecast the number of cases and deaths. We used an iterated filtering (IF) framework to estimate the model transmission parameters using the reported data across 281 municipalities from March to late October in locations with more than 50 reported deaths and cases in Colombia.

Genomic epidemiological models describe pathogen evolution across fitness valleys.

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment.

A mixed-methods study on the design of Artificial Intelligence and data science-based strategies to inform public health responses to COVID-19 in different local health ecosystems: A study protocol for COLEV.

Artificial Intelligence (AI) and data science research are promising tools to better inform public policy and public health responses, promoting automation and affordability. During the COVID-19 pandemic, AI has been an aid to forecast outbreak spread globally. The overall aim of the study is to contribute to the ongoing public health, socioeconomic, and communication challenges caused by COVID-19.

Disentangling snakebite dynamics in Colombia: How does rainfall and temperature drive snakebite temporal patterns?

The role of climate driving zoonotic diseases' population dynamics has typically been addressed via retrospective analyses of national aggregated incidence records. A central question in epidemiology has been whether seasonal and interannual cycles are driven by climate variation or generated by socioeconomic factors. Here, we use compartmental models to quantify the role of rainfall and temperature in the dynamics of snakebite, which is one of the primary neglected tropical diseases.

How disease risk awareness modulates transmission: coupling infectious disease models with behavioural dynamics.

Epidemiological models often assume that individuals do not change their behaviour or that those aspects are implicitly incorporated in parameters in the models. Typically, these assumptions are included in the contact rate between infectious and susceptible individuals. However, adaptive behaviours are expected to emerge and play an important role in the transmission dynamics across populations.

Deciphering the introduction and transmission of SARS-CoV-2 in the Colombian Amazon Basin.

Background: The SARS-CoV-2 pandemic has forced health authorities across the world to take important decisions to curtail its spread. Genomic epidemiology has emerged as a valuable tool to understand introductions and spread of the virus in a specific geographic location.

Methodology/principal Findings: Here, we report the sequences of 59 SARS-CoV-2 samples from inhabitants of the Colombian Amazonas department.

Estimating snakebite incidence from mathematical models: A test in Costa Rica.

Background: Snakebite envenoming is a neglected public health challenge that affects mostly economically deprived communities who inhabit tropical regions. In these regions, snakebite incidence data is not always reliable, and access to health care is scare and heterogeneous. Thus, addressing the problem of snakebite effectively requires an understanding of how spatial heterogeneity in snakebite is associated with human demographics and snakes' distribution.

Development, environmental degradation, and disease spread in the Brazilian Amazon.

The Amazon is Brazil's greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil's president brought disputes over development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation.

The rise and fall of malaria under land-use change in frontier regions.

Land-use change is the main force behind ecological and social change in many countries around the globe; it is primarily driven by resource needs and external economic incentives. Concomitantly, transformations of the land are the main drivers for the emergence and re-emergence of malaria. An understanding of malaria population dynamics in transforming landscapes is lacking, despite its relevance for developmental and public health policies.

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India.

Background: The world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management.

Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity.

Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments.

Temperature and population density determine reservoir regions of seasonal persistence in highland malaria.

A better understanding of malaria persistence in highly seasonal environments such as highlands and desert fringes requires identifying the factors behind the spatial reservoir of the pathogen in the low season. In these 'unstable' malaria regions, such reservoirs play a critical role by allowing persistence during the low transmission season and therefore, between seasonal outbreaks. In the highlands of East Africa, the most populated epidemic regions in Africa, temperature is expected to be intimately connected to where in space the disease is able to persist because of pronounced altitudinal gradients.