Biology subjects

Santos-Vega, M.

Publications and source records attributed to Santos-Vega, M..

9 recordsLinked to original sources

bioRxiv2026

Temperature variation as a driver of Wolbachia release efficacy: implications for dengue control in warming climates

BackgroundWolbachia-based control methods reduce dengue transmission by suppressing Aedes aegypti populations or blocking viral replication, yet their effectiveness across the climatic conditions of endemic regions remains poorly understood. Seasonal and interannual temperature changes shape mosquito dynamics, but how Wolbachia releases perform during anomalous events such as El Nino or heatwaves is largely unknown--a gap that limits our ability to optimize release strategies and predict intervention success across different climates. Methodology/Principal FindingsTo address this gap, we built a mathematical modeling framework that explicitly incorporates temperature-dependent Wolbachia parameters together with the seasonal and interannual climate variability characteristic of dengue-endemic regions, coupling a detailed Wolbachia dynamics model with a susceptible-infectious-recovered (SIR) epidemiological model to evaluate Wolbachia establishment, persistence, and stability under different thermal regimes and trace their downstream impact on disease spread. Higher temperatures eroded both Wolbachia establishment and long-term persistence, sharply narrowing the range of effective release strategies as conditions approached 30 {degrees}C. Seasonality added a further layer of complexity: the timing of thermal stress relative to Wolbachia frequency, not merely its magnitude, determined whether population replacement succeeded. Interannual shifts, progressive warming, widening seasonal swings, and displaced thermal peaks, each eroded Wolbachia prevalence and stability, with effects that compounded over successive years. Dengue transmission tracked these dynamics closely, with warmer conditions producing larger, earlier outbreaks, and intervention success hinging on how release timing, frequency, and targeting were matched to local thermal conditions. Conclusions/SignificanceAs extreme heat events become more frequent under climate change, release programs that ignore local thermal conditions risk falling short where dengue control is most needed. By elucidating the mechanistic interplay among temperature, Wolbachia, and dengue, our findings help refine Wolbachia release programs to suit different climatic conditions, thereby strengthening dengue control as climate variability intensifies. Author summaryDengue sickens hundreds of millions of people each year, and releasing mosquitoes carrying the naturally occurring bacterium Wolbachia, which blunts the viruss spread, has become one of the most promising tools for fighting it. Yet one factor that decides whether these releases succeed or fail is routinely overlooked: temperature. We built a mathematical model linking Wolbachia biology and mosquito population dynamics to temperature, to ask a practical question: which release strategies work under real-world, changing climate conditions? Heat narrowed the margin for success. Higher temperatures shrank the range of effective interventions and slowed the replacement of wild mosquitoes with Wolbachia-carrying ones. Timing mattered just as much as intensity: releases launched before peak heat allowed Wolbachia to establish at higher levels, before thermal stress eroded its fitness benefits. And success was not permanent--growing year-to-year temperature swings could destabilize Wolbachia populations even after they had become established, threatening long-term disease control. The public-health stakes were stark: Wolbachia cut peak dengue cases by 54.6% at 25{degrees}C, but by only 10% at 30{degrees}C. For the communities most burdened by dengue, these results carry an urgent message. As climate change drives temperatures upward across endemic regions, Wolbachia programs designed without accounting for local thermal conditions risk underperforming precisely where they are needed most. Effective deployment requires climate-sensitive planning, adaptive release schedules, and continued investment in field-validated models that reflect the realities of a warming world.

ecology↗

bioRxiv2026

Beyond biodiversity loss defaunation: cascades effects in zoonotic disease ecology

Defaunation, defined as the loss or severe decline of animal populations, is increasingly recognized as a major dimension of global environmental change, yet its role in zoonotic disease ecology remains poorly understood. Although defaunation significantly influences ecological dynamics, current metrics often focus on species loss without fully addressing its cascading impacts, which can affect ecological processes such as zoonotic disease transmission. In this perspective, we propose a defaunation-cascade framework linking anthropogenic pressure to zoonotic pathogen dynamics through four ecological steps: host trait filtering, abundance restructuring, interaction rewiring, and altered pathogen circulation or proliferation, and potential spillover hazard. We illustrate this framework by using a global review of empirical studies and combining georeferenced data on disease prevalence with environmental and human-related factors. Our exploratory models suggest pathogen-specific associations: parasitic and bacterial prevalence were more strongly associated with anthropogenic pressure and mammal diversity metrics, whereas viral prevalence showed weaker support. We contend that incorporating defaunation cascades into One Health surveillance will improve ecological understanding of pathogen circulation and enhance the ecological accuracy and predictive power of zoonotic disease models, thereby identifying landscapes where faunal simplification may elevate spillover hazard.

ecology↗

bioRxiv2026

From low to high transmission: Diversity-dependent responses of Plasmodium falciparum population structure to transmission intensity

Genetic surveillance is increasingly used to track malaria transmission, yet genomic metrics can respond nonlinearly to changes in transmission intensity and depend on the diversity already present in the parasite population. Here, we present a stochastic agent-based model of hu-man-mosquito transmission that integrates SEIS-like epidemiological dynamics with within-host Plasmodium falciparum haplotype dynamics. By varying the maximum mosquito biting rate and the initial parasite diversity, we examine how transmission intensity and standing diversity jointly shape mixed infections, recombination, and long-term population structure across a continuous transmission gradient. Our study revealed a sequential pattern in which increasing biting intensity first increases infection prevalence and multiplicity of infection, then expands opportunities for outcrossing, and only thereafter increases effective recombination and recombinant haplotype generation. These responses are strongest in low- to intermediate transmission and tend to plateau at higher transmission levels. Initial population diversity constrains the amount of diversity that can be maintained and the magnitude of recombination output, while temporal trajectories show that haplotype evenness can pass through transient non-equilibrium phases before stabilizing. Together, these results show that the structure of the parasite population is shaped not by trans-mission intensity alone but by its interaction with standing genetic diversity. Furthermore, this study works to clarify when and how genomic metrics reliably reflect transmission conditions across heterogeneous malaria settings.

genetics↗

bioRxiv2026

ENSO-driven climate variability reconfigures the altitudinal frontier of dengue risk in the Andes

Despite the high burden of dengue in Latin America, high elevations have historically protected megacities such as Mexico City, Quito, and Bogota. Climate change is expected to shift elevational suitability frontiers, yet the mechanisms governing disease expansion into highland regions and the timescales over which it occurs remain poorly characterized. Using spatiotemporal decomposition techniques, we identified a mechanistic cascade linking (1) the El Nino-Southern Oscillation (ENSO) to local Colombian climate, accounting for [~]85% of interannual temperature variability and [~]53% of rainfall variability, and (2) local climate to dengue dynamics, accounting for [~]66-76% of variation in incidence and [~]44-55% of its altitudinal range. Multiple lines of evidence, including spatial ENSO signatures across Andean ridges, temporal predictive performance, and vectorial-capacity modeling, identified the local temperature expression of the ENSO teleconnection as the dominant driver of transmission. During warm ENSO phases, dengue incidence increases exponentially and transmission expands into higher elevations. This shifts the altitudinal distribution of dengue transmission upward, exposing immunologically naive populations in highland areas that were previously considered unsuitable. Mechanistically, this altitudinal shift arises because a coherent warming across elevational strata disproportionately increases transmission in highland regions, where small temperature increments produce the largest increase in vectorial capacity. These findings challenge the view that disease expansion is primarily a gradual response to long-term warming and highlight the importance of climate variability for disease projection, attribution, and public health preparedness. Significance statementWhile increasing mean temperatures are a known threat to the changing landscape of infectious diseases, this study reveals that interannual climate variability can be a more immediate driver of disease burden and expansion. We show that the El Nino phenomenon produces local temperature anomalies in Colombia that exponentially increase dengue cases and extend dengues reach into high-altitude areas, potentially exposing millions of immunologically naive people. This finding is highly relevant to the elevated dengue-free megacities in Latin America, such as Mexico City, Quito, and Bogota. By shifting the focus from multi-decadal trends to interannual climate variability, this paper provides a methodological blueprint for more accurate predictions of how infectious diseases will behave as our climate becomes increasingly unstable.

ecology↗

bioRxiv2021

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. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

evolutionary biology↗

bioRxiv2021

Estimating real snakebite incidence in Colombia by using mathematical modelling and statistical inference.

Snakebite envenoming is a Neglected Tropical Disease affecting mainly deprived populations. Its burden is normally underestimated because patients prefer to seek for traditional medicine. Thus, applying strategies to optimize disease management and treatment delivery is difficult. We propose a framework to estimate snakebite incidence at a fine political scale based on available data, testing it in Colombia. First, we produced snakebite fine-scale risk maps based on the most medically important venomous snake species (Bothrops asper and B. atrox). We validated them with reported data in the country. Then, we proposed a generalized mixed effect model that estimates total incidence based on produced risk maps, poverty indexes, and an accessibility score that reflects the struggle to reach a medical center. Finally, we calibrated our model with national snakebite reported data from 2010 to 2019 using a Markov chain Monte Carlo (MCMC) algorithm and estimated underreporting based on the total incidence estimation. Our results suggest that 10.3% of total snakebite cases are not reported in Colombia and do not seek medical attention. The Orinoco and Amazonian regions (east of Colombia) share a high snakebite risk with a high underreporting. Our work highlights the importance of multidisciplinary approaches to face snakebite.

ecology↗

bioRxiv2021

Entangling snakebite dynamics: the spatiotemporal role of rainfall on snake envenoming in Colombia

The role of climate forcing on the population dynamics of infectious diseases has typically been addressed via retrospective analyses of aggregated incidence records over whole political regions. A central question in epidemiology has been whether seasonal and interannual cycles are driven by climate variation, or instead generated by other factors such as poverty or underreporting. Here, we use process-based models to determine the role of rainfall in the dynamics of snakebite, which is one of the main neglected tropical diseases around the world. We combined space-time datasets of snakebite incidence and rainfall for Colombia in combination with stochastic epidemiological models and iterated filtering methods to show the response to rainfall forcing, specifically, modulating the encounter frequency with venomous snakes. We identified six zones with different rainfall patterns to demonstrate that the relationship between rainfall and snakebite incidence was heterogeneous. Rainfall only drives snakebite incidence in regions with marked dry seasons, where rainfall becomes the limiting resource. In addition, the encounter frequency also differs between regions, and it is higher in regions where Bothrops atrox can be found. Our results show how the heterogeneous spatial distribution of snakebite risk seasonality in the country may be related to important traits of venomous snakes natural history. SIGNIFICANCE STATEMENTThe association between seasonal climatic variables and diseases epidemiology has helped to understand disease burden under changing environments. For example, for several tropical zoonotic diseases rainfall has been identified as a critical covariate inducing incidence seasonality. Snakebite envenoming is a disease that affects mostly economically deprived populations, and the availability of treatment is scarce. However, the role of environmental factors on snakebite is still missing in the literature. We formulated an epidemiological model to quantify the role of rainfall on snakebite seasonality throughout Colombia. We found that rainfall has a significant effect on incidence in places with a marked dry season (Caribbean and Orinoco plains), but in areas without dry season (Amazonian basin and southwestern Colombia) incidence exhibits no seasonality. This study is the first epidemiological modeling approach to snakebite and underscores the importance of rainfall as the limiting resource in this system. Thus, it is important to consider the interaction between climate forcing and venomous snakes ecology as determinants of envenomation risk.

ecology↗

bioRxiv2021

THE UNAPPARENT EFFECT OF CLIMATE FORCING ON URBAN AMOEBIASIS IN MEXICO CITY

AO_SCPLOWBSTRACTC_SCPLOWDespite advances in the provision of sanitation infrastructure in cities, diarrheal-related illnesses continue to be a global burden. In cities of the developing world, explanations for the persistence of diarrheal-related diseases revolve around the role of sanitation, poverty, and individual behavior. Less is known about the role of climate in forcing the inter-annual variability of transmission. We quantified the contribution of rainfall to the transmission of a diarrhoeal disease caused by the protozoan Entamoeba histolytica. We formulated a process-based model of the population dynamics of Entamoeba histolytica in 6 municipalities of Mexico City, and we reconstructed the interannual variability of the observed cases of amebiasis between 2005 and 2012. Using inference methods for non-linear systems, we estimated that 10% of the susceptible individuals were infected in early 2005 and 90% of those infections were causally related to the exposure to the environmental stage of the pathogen after rainfall events. The magnitude of these results underscores the importance of considering the interaction between climate forcing and water management as ecological determinants of health in megacities.

ecology↗

bioRxiv2019

Local climate and social inequality drive spatio-temporal variation in malaria risk across a complex urban landscape

BackgroundCities are becoming increasingly important habitats for mosquito-borne infections. The pronounced heterogeneity of urban landscapes challenges our understanding of the spatio-temporal dynamics of these diseases, and of the influence of climate and socio-economic factors at different spatial scales. Here, we quantify this joint influence on malaria risk by taking advantage of an extensive dataset in both space and time for reported Plasmodium falciparum cases in the city of Surat, Northwest India. MethodsWe analyzed 10 years of monthly falciparum cases resolved at three nested spatial resolutions (for 7 zones, 32 units and 478 workers units subdivisions, respectively). With a Bayesian hierarchical mixed model that incorporates effects of population density, poverty, humidity and temperature, we investigate the main drivers of spatio-temporal malaria risk at the intermediate scale of districts. The significance of covariates and the model fit is then examined at lower and higher resolutions. FindingsThe spatial variation of urban malaria cases is strongly stationary in time, whereby locations exhibiting high and low yearly cases remain largely consistent across years. Local socio-economic variation can be summarized with two main principal components, representing poverty and population density respectively. The model that incorporates these two factors together with local temperature and global relative humidity, best explains monthly malaria patterns at the intermediate resolution. The effects of local temperature and population density remain significant at the finest spatial scale. We further identify the specific areas where such increased resolution improves model fit. InterpretationMalaria risk patterns within the city are largely driven by fixed spatial structures, highlighting the key role of local climate conditions and social inequality. As a result, malaria elimination efforts in the Indian subcontinent can benefit from identifying, predicting and targeting disease hotspots within cities. Spatio-temporal statistical models for the mesoscale of administrative units can inform control efforts, and be complemented with bespoke plans in the identified areas where finer scale data could be of value. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSUrban areas have become the new dominant ecosystem around the globe. Developing countries comprise the most urbanized regions of the world, with 80% of their population living in cities and an expected increase to 90% by 2050. The large and heterogeneous environments of today challenge the understanding and control of infectious disease dynamics, including of those transmitted by vectors. Malaria in the Indian subcontinent has an important urban component given the existence of a truly urban mosquito vector Anopheles stephensi. A literature search in Mendeley of "urban malaria" and "India" returned 161 publications, in their majority on diagnostics or brief reports on the disease, and on cross-sectional rather than longitudinal studies addressing the spatio-temporal variation of disease risk for a whole city, the subject of our work. A relevant exception is a study for the city of Ahmedabad; this not address multiple seasons across different spatial scales, and climatic conditions are not considered jointly with socio-economic drivers in the modeling. A second Mendeley search on A. stephensi returned 11 publications into two distinct groups: early entomological studies for India and recent reports of the mosquito in the Horn of Africa. This geographical expansion makes the specter of urban malaria a future possibility for the African continent where the disease remains so far rural and peri-urban. Added value of this studyThis paper relies on an extensive surveillance data set of Plasmodium falciparum cases for Surat (India) to investigate the variation and drivers of malaria risk in an heterogenous urban environment. A statistical model for the spatio-temporal variability of cases is developed, which includes both climatic and socio-economic drivers, with the latter summarized into two major axes of variation. Model fits are compared across three spatial resolutions, ranging from a few zones to a few hundred units. Seasonal hotspots are shown to be largely stationary in time, which allows identification of dominant drivers, including population density and local temperatures, whereas humidity acts globally modulating year-to-year burden. More granular statistical models and datasets like the one analyzed here are needed to capture the effects of socioeconomic and climatic drivers, and to predict current and future malaria incidence patterns within cities. Implications of all the available evidenceThe analysis identifies relevant resolution which can vary across the city for targeted intervention, including vector control, that would focus on reducing and eliminating transmission hotspots. The modeling framework, incorporating predictors representing climate at local vs. aggregate levels, and major axes of socio-economic variation, should apply to other vector-borne diseases and other cities for which surveillance records are available. The importance of spatially-explicit and sustained surveillance data for informing these models cannot be overstated.

ecology↗