top of page
PUBLICATIONS
Investigating antibody cross-reactivity and transmission dynamics of alphaviruses and flaviviruses using a multiplex serological assay
Global variation in heat stroke mortality: Evidence from a multi-country study
Ethical considerations related to drone use for environment and health research: a scoping review
Drone-based geospatial prediction modeling identifies Fasciola hepatica infection risk in the Cusco Highlands of Peru
![Several studies have explored the short-term effects of environmental stressors on coronavirus disease 2019 (COVID-19) transmission and severity. However, evidence on the interactive effects of meteorological conditions and air pollution remains limited and geographically variable. We therefore aimed to quantify the independent and interactive effects of short-term exposure to humidex, a composite index of temperature and relative humidity, and fine particulate matter ≤ 2.5 μm (PM2.5) on daily COVID-19 incidence across multiple cities and in multiple countries. Daily time-series data on confirmed COVID-19 cases, meteorological factors, and PM2.5 concentrations were collected from 439 cities in 22 countries during January 2020–August 2022 as part of the Multi-Country Multi-City Collaborative Research Network. A two-stage design was applied: first, city-specific quasi-Poisson models with distributed lag non-linear models estimated exposure–response associations; second, multilevel random-effects meta-analyses pooled city-specific estimates. Effect modification by PM2.5 was assessed using a product term between non-linear humidex function and linear PM2.5 function. Approximately 95.1 million confirmed COVID-19 cases were analyzed. Lower humidex values (0.1 °C versus 15.1 °C) were associated with increased daily cases (relative risk [RR]: 1.1192, 95% confidence interval [CI]: 1.0214–1.2262). A 10 μg/m3 increase in PM2.5 over the current and preceding 2 days was associated with a modest increase in daily cases (RR: 1.0079, 95% CI: 1.0001–1.0161). No statistically significant interaction between humidex and PM2.5 was observed. Short-term exposure to cold–dry conditions and elevated PM2.5 independently increased COVID-19 incidence, highlighting the need to consider both thermal environment and air quality when designing climate-resilient public health responses. These findings enhance understanding of how climate-related environmental stressors influence COVID-19 transmission.](https://static.wixstatic.com/media/6bf5a0_ab8ec50259b8402081f97580d9b9b741~mv2.jpg/v1/fill/w_1490,h_840,q_90,enc_avif,quality_auto/6bf5a0_ab8ec50259b8402081f97580d9b9b741~mv2.jpg)
The joint impact of temperature, humidity, and air pollution on COVID-19 incidence: A multi-country time-series study in 439 cities
Genomic Epidemiology of SARS-COV-2 in Peru, 2020-2024
Data Resource Profile: Climate and Enteric Diseases Research Project (ClimED)
Spatiotemporal co-distribution and time lagged cross correlation of malaria and dengue in Loreto, Peru
![Fine particulate matter (PM2.5) is a leading global health risk. Latin American cities exhibit some of the world’s highest urban PM2.5 levels, yet studies of neighborhood-level PM2.5 exposure and associated disparities in the region are limited. Methods. We conducted a cross-sectional ecological analysis of 53 041 neighborhoods across 340 cities in eight Latin American countries, leveraging the Salud Urbana en America Latina study dataset. Annual PM2.5 concentrations were derived from satellite data and linked to socioeconomic and urban characteristics. A multilevel model analyzed associations between neighborhood PM2.5 levels and neighborhood- and city-level characteristics. Results. The median annual neighborhood PM2.5 concentration was 18.49 µg m−3. Of the 256 million residents, all lived in neighborhoods with ambient PM2.5 concentrations that exceeded the 2021 World Health Organization guidelines (5 µg m−3). Variability was greatest between cities (54.3% of total variance), but substantial within-city variation (26% of variance) was observed. Higher neighborhood PM2.5 levels were associated with higher neighborhood educational attainment (mean difference [MD] comparing top to bottom tertile = 0.17 µg m−3), higher neighborhood intersection density (MD comparing top to bottom tertile = 0.17 µg m−3), and older cities (MD comparing top to bottom tertile = 1.45 µg m−3). Lower neighborhood PM2.5 levels were related to higher neighborhood population density (MD comparing top to bottom tertile = − 0.55 µg m−3), more greenness (MD comparing top to bottom tertile = − 0.76 µg m−3), and larger distance from city centers (MD comparing top to bottom tertile = − 0.86 µg m−3). Conclusions. Neighborhoods with higher PM2.5 concentrations tended to have higher educational attainment, more intersections, and be located in older cities, while lower concentrations were associated with denser populations, more green space, and greater distance from city centers. Our findings reveal important within-city heterogeneity in PM2.5 and the factors associated with it, suggesting strategies to mitigate air pollution within cities.](https://static.wixstatic.com/media/6bf5a0_0c048eb1cbdb48e59b358020ed447ea2~mv2.jpg/v1/fill/w_1490,h_840,q_90,enc_avif,quality_auto/6bf5a0_0c048eb1cbdb48e59b358020ed447ea2~mv2.jpg)
Urban and Socioeconomic Disparities in PM2.5 Exposure Across 340 Latin American Cities
Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries
FocaL mass drug Administration for Plasmodium vivax Malaria Elimination (FLAME): study protocol for an open-label cluster randomized controlled trial in Peru
![The presence of benzene, toluene, ethylbenzene, and xylene isomers (BTEX) in the environment is of increasing concern due to their toxicity and ubiquity. Although the adverse health effects of BTEX exposure have been documented, robust epidemiological evidence from large-scale, multicountry studies using advanced exposure assessment methodologies remains scarce. We aimed to assess the association of short-term ambient exposure to individual BTEX components and their mixture with daily total, cardiovascular, and respiratory mortality on a global scale.
Methods
Daily data on mortality, meteorological factors, and air pollution were collected from 757 locations across 46 countries or regions. Data on individual chemicals (ie, benzene, toluene, xylenes [summation of ethylbenzene, m-xylene, p-xylene, and o-xylene]) and the aggregate mixture (ie, BTEX) were estimated using a chemistry–climate model. We examined the short-term associations of each individual chemical as well as the BTEX mixture with daily total, cardiovascular, and respiratory mortality in a multicountry framework. Using a two-stage time-series design, we first applied generalised additive models with a quasi-Poisson distribution to obtain location-specific associations, which were subsequently pooled using random-effects meta-analysis. Two-pollutant models were used to assess the independent effects of BTEX after adjusting for co-pollutants (PM2·5, PM10, nitrogen dioxide, sulphur dioxide, ozone, and carbon monoxide). Additionally, we assessed the overall exposure–response curves with spline terms.
Findings
An IQR increment of BTEX concentration on lag 0–2 days (3-day moving average of the present day and the previous 2 days) was associated with increases of 0·57% (95% CI 0·49–0·65), 0·42% (0·30–0·54), and 0·68% (0·50–0·86) in total, cardiovascular, and respiratory mortality, respectively. The corresponding effect estimates for an IQR increment in individual chemicals (benzene, toluene, and xylenes) were 0·38–0·61%, 0·44–0·70%, and 0·41–0·65%, respectively. The associations remained significant after adjusting for co-pollutants, with a general decline in magnitude, except for a slight increase after adjustment for ozone. The shape of the exposure–response curves for all pollutants and causes of death was almost linear, with steeper slopes at low concentrations and no discernible thresholds.
Interpretation
This global study provides novel evidence linking short-term exposure to ambient BTEX, both individually and as a mixture, with increased daily total, cardiovascular, and respiratory mortality. Our findings underscore the need for comprehensive air pollution mitigation policies, including stringent controls on BTEX emissions, to protect public health.](https://static.wixstatic.com/media/6bf5a0_d337d849ff01405e93cf3fdcb4745ac5~mv2.jpg/v1/fill/w_1490,h_840,q_90,enc_avif,quality_auto/6bf5a0_d337d849ff01405e93cf3fdcb4745ac5~mv2.jpg)
Associations of ambient exposure to benzene, toluene, ethylbenzene, and xylene with daily mortality in 757 global locations
Short-term association between hot nights and mortality: a multicountry analysis in 178 locations considering hourly ambient temperature
Evidence-based decision-making for malaria elimination: Applying the Freedom From Infection statistical framework in five malaria eliminating countries
Two-Stage Interrupted Time Series Analysis with Machine Learning: Evaluating the Health Effects of the 2018 Wildfire Smoke Event in San Francisco County as a Case Study
![Dengue is currently the most significant vector-borne disease in Peru, with its incidence increasing markedly over the past few years. In particular, 2023 saw a substantial rise, with 251,605 confirmed cases reported, making it the highest incidence recorded in the country’s history [1]. Although cases were reported in Peru during the 1950s, the epidemic in 1990 was the first laboratory confirmation of dengue indigenous transmission in Peru [2]. Confirmed cases in 2023 were approximately 9-fold the average number during the previous 5 years (29,841 confirmed cases) and 4.2-fold the number during 2017 (59,303 confirmed cases), the year of the largest previous national dengue outbreak [3]. We hypothesized that, in Peru, the apparent confluence of urbanization, climate change, and increased human migration has led to the worst dengue epidemic in the country’s history, peaking in recent years. In this comment, we aimed to describe the rapid geographic expansion of local community transmission of dengue in distinct natural regions of Peru over the past two decades, particularly toward districts that have historically been free of dengue transmission.](https://static.wixstatic.com/media/6bf5a0_914edb6304914a65837d863bf80f2080~mv2.png/v1/fill/w_1490,h_840,q_90,enc_avif,quality_auto/6bf5a0_914edb6304914a65837d863bf80f2080~mv2.png)
Rapid geographic expansion of local dengue community transmission in Peru
Social disparities in neighborhood flood exposure in 44,698 urban neighborhoods in Latin America
Practical Control of Mosquitoes as Disease Vectors - The Use of Drones for Mosquito Surveillance and Control
Regional variation in the role of humidity on city-level heat-related mortality
![Background
Heat can vary spatially within an urban area. Individual-level heat exposure may thus depend on an individual’s day-to-day travel patterns (also called mobility patterns or activity space), yet heat exposure is commonly measured based on place of residence.
Objective
In this study, we compared measures assessing exposure to two heat indicators using place of residence with those defined considering participants’ day-to-day mobility patterns.
Methods
Participants (n = 599; aged 35-80 years old [mean =59 years]) from San Diego County, California wore a GPS device to measure their day-to-day travel over 14-day intervals between 2014-10-17 and 2017-10-06. We measured exposure to two heat indicators (land-surface temperature [LST] and air temperature) using an approach considering their mobility patterns and an approach considering only their place of residence. We compared participant mean and maximum exposure values from each method for each indicator.
Results
The overall mobility-based mean LST exposure (34.7 °C) was almost equivalent to the corresponding residence-based mean (34.8 °C; mean difference in means = −0.09 °C). Similarly, the mean difference between the overall mobility-based mean air temperature exposure (19.2 °C) and the corresponding residence-based mean (19.2 °C) was negligible (−0.02 °C). Meaningful differences emerged, however, when comparing maximums, particularly for LST. The mean mobility-based maximum LST was 40.3 °C compared with a mean residence-based maximum of 35.8 °C, a difference of 4.51 °C. The difference in maximums was considerably smaller for air temperature (mean = 0.40 °C; SD = 1.41 °C) but nevertheless greater than the corresponding difference in means.
Impact
As the climate warms, assessment of heat exposure both at and away from home is important for understanding its health impacts. We compared two approaches to estimate exposure to two heat measures (land surface temperature and air temperature). The first approach only considered exposure at home, and the second considered day-to-day travel. Considering the average exposure estimated by each approach, the results were almost identical. Considering the maximum exposure experienced (specific definition in text), the differences between the two approaches were more considerable, especially for land surface temperature.](https://static.wixstatic.com/media/6bf5a0_8194eb9490da4e68855464704b54f40e~mv2.webp/v1/fill/w_1490,h_840,q_90,enc_avif,quality_auto/6bf5a0_8194eb9490da4e68855464704b54f40e~mv2.webp)
Is home where the heat is? comparing residence-based with mobility-based measures of heat exposure in San Diego, California
Rainfall events and daily mortality across 645 global locations: two stage time series analysis
Mortality burden and economic loss attributable to cold and heat in Central and South America
Impacts of land-use and land-cover changes on temperature-related mortality
The role of connectivity on malaria dynamics across areas with contrasting control coverage in the Peruvian Amazon
Meteorological factors, population immunity, and COVID-19 incidence: A global multi-city analysis
bottom of page