Biology subjects

Kraemer, M. U. G.

Publications and source records attributed to Kraemer, M. U. G..

11 recordsLinked to original sources

bioRxiv2026

Dairy cattle movement networks govern the spread and persistence of H5N1 B3.13 in the United States

Avian influenza virus H5N1 is predominantly found in wild and domestic birds. H5N1 genotype B3.13 was first detected in United States dairy cattle in March 2024 and spread through much of the country during 2024 and 2025, resulting in the largest known H5N1 outbreak in domestic mammals. By analysing viral genomic data jointly with historical cattle movement patterns, we find that live cattle movement is the predominant contributor to H5N1 spatial spread, rather than wild or domestic birds. Using phylogeographic methods we estimate that >40% of interstate viral transmissions occurred before B3.13's first detection and >70% occurred before interstate dairy cattle movement restrictions were implemented in April 2024. After this implementation, interstate transmission slowed but within-state spread persisted, driven by local cattle network density and movement volume. Our epidemic simulations demonstrate that the connectivity of counties within and around the Texas Panhandle - where the earliest cases were documented - predisposed the region to become an outbreak epicentre. Counterfactual simulations indicate that interstate restrictions needed to have begun 2-3 months earlier in order to limit the epizootic substantively, given the extent of cryptic spread before detection. Network-informed interventions outperformed geographically-defined containment, but response speed (rather than intervention strength) was the limiting factor in our epidemic models, underscoring the need for surveillance systems capable of detecting pathogen emergence before widespread dissemination.

evolutionary biology↗

bioRxiv2026

Phylodynamic analysis reveals asymmetric and accelerating global spread of dengue virus

Dengue virus (DENV) continues to expand globally, with increasing incidence in both endemic and non-endemic countries. Leveraging a large global dataset of DENV genomes starting from the 1940s, we reconstructed global and regional patterns of DENV spread using phylogeographic and phylodynamic methods. Our analyses reveal that the current global diversity of urban DENV originated in Asia in the first half of the 20th century. During the more than 100 years since, we find that the highest density of between-country spread occurs within Asia and the region continues to be a global source, seeding transmission in Africa and the Americas. Global spread is, however, not balanced. Even though there is more travel to South America, we show that DENV lineages primarily enter North America (mostly from South Asia) through a link defined by seasonal synchrony across the Northern Hemisphere. Along with a substantial increase in global travel starting ~2010, the rate of spread to the Americas is increasing, establishing new lineages associated with large recent outbreaks. DENV lineages do not frequently spread back to Asia from the Americas or Africa, and we posit this is due to higher genetic diversity in Asia, leading to stiffer competition for invading lineages. Within the Americas, the network of DENV dispersal initiates in North America, primarily the Caribbean, and then is maintained by major hubs in South America. Overall, we find that travel volume, rather than climate factors, is mostly responsible for long-term patterns of DENV spread globally and within the Americas. Our results highlight key nodes in the global dynamics of DENV lineages, and suggest spread will continue to accelerate in a more connected world.

genomics↗

bioRxiv2026

The emergence and molecular evolution of H5N1 influenza viruses in United States dairy cattle

Prior to 2024, highly pathogenic avian influenza H5N1 clade 2.3.4.4b viruses circulated predominantly in wild birds and poultry. In 2024 and 2025, 2.3.4.4b genotypes B3.13 and D1.1 were detected in United States dairy cattle. Using whole-genome and segment-specific phylodynamic inference, we estimate that B3.13 and D1.1 spilled over from wild birds into dairy cattle in late 2023 and late 2024, respectively. Spillover occurred shortly after the formation of the reassortant genotypes and was followed by months of cryptic transmission prior to detection. We found that both B3.13 and D1.1 evolved at higher rates in cattle relative to birds, primarily due to relaxed purifying selection. Site-specific analyses identified genomic sites under positive selection in cattle relative to birds, indicating adaptation and likely contributing to improved viral fitness after spillover. Intensified genomic surveillance in dairy cattle is essential as population immunity introduces additional selection pressures, with ever-changing risk for human emergence.

evolutionary biology↗

bioRxiv2025

Disaggregation Regression and Multi-Model Evaluation for Predicting Dengue Risk in Africa

Dengue risk mapping is essential for estimating disease burden, and informing targeted surveillance and control efforts. Current approaches to risk mapping vary widely in their methodology, data sources, output metrics and applications. Many existing approaches focus on predicting ecological suitability and produce high-resolution risk maps based on environmental conditions, yet high-resolution incidence maps remain scarce, leaving a critical gap in guiding precise, location-specific interventions. The prediction of disease incidence or transmission intensity remains relatively uncommon in disease ecology, largely due to data limitations, reporting biases, and the inherent complexity that arises from transmission dynamics. In this study, we applied disaggregation regression modelling to downscale aggregated dengue case data from 14 countries in Central and South America, generating fine-resolution incidence estimates that we subsequently projected onto the African continent. We then compared the resulting predictions from the incidence-based risk map with three widely used approaches: vector suitability index, dengue environmental suitability index, and mechanistic transmission potential (Index P). The disaggregation model achieved relatively strong predictive accuracy within the training region (mean correlation = 0.72) and showed partial alignment with reported burden across Africa (Spearman {rho} = 0.33). Other risk maps exhibited similar or weaker correlations with reported cases in Africa, including {rho} = 0.33 for dengue environmental suitability, {rho} = 0.32 for transmission potential and {rho} = 0.23 for Aedes aegypti suitability. Disaggregation regression offers a valuable tool for translating reported case data into spatially explicit estimates of burden, bridging the gap between ecological risk and epidemiological relevance. While spatial agreement was high in parts of coastal West Africa across the different risk map approaches, notable divergences highlight the distinct assumptions underlying each framework. Authors SummaryDengue is a mosquito-borne viral disease with expanding global impact. Accurately mapping dengue risk is essential for identifying areas of high transmission and targeting interventions effectively. Most current approaches to mapping dengue risk focus on environmental suitability for the virus or its mosquito vector, rather than estimating actual disease burden. In this study, we used an incidence-based approach; disaggregation regression, to estimate dengue cases at high spatial resolution using national and regional case data from Latin America. We then applied the model to Africa, where surveillance data are limited, and compared its predictions to three other common types of dengue risk maps. Our results showed that while all approaches provided some insight into geographic risk patterns, they often highlighted different areas as priorities. Our incidence-based model captured both where dengue might occur and how intense transmission may be, helping bridge the gap between environmental and ecological suitability of transmission and real-world disease burden. This approach can support more informed decision-making in areas with limited surveillance and guide targeted control efforts.

ecology↗

bioRxiv2022

Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico

Over 200 different SARS-CoV-2 lineages have been observed in Mexico by November 2021. To investigate lineage replacement dynamics, we applied a phylodynamic approach and explored the evolutionary trajectories of five dominant lineages that circulated during the first year of local transmission. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in Mexico. Lineages B.1.1.222 and B.1.1.519 exhibited similar dynamics, constituting clades that likely originated in Mexico and persisted for >12 months. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. For the largest B.1.617.2 clades, we further explored viral lineage movements across Mexico. Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.

evolutionary biology↗

bioRxiv2018

Modelling the distribution of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competitive effects

Florida faces the challenge of repeated introduction and autochthonous transmission of arboviruses transmitted by Aedes aegypti and Aedes albopictus. Empirically-based predictive models of the spatial distribution of these species would aid surveillance and vector control efforts. To predict the occurrence and abundance of these species, we fit mixed-effects zero-inflated negative binomial regression to a mosquito surveillance dataset with records from more than 200,000 trap days, covering 73% of the land area and ranging from 2004 to 2018 in Florida. We found an asymmetrical competitive interaction between adult populations of Aedes aegypti and Aedes albopictus for the sampled sites. Wind speed was negatively associated with the occurrence and abundance of both vectors. Our model predictions show high accuracy (72.9% to 94.5%) in the validation tests leaving out a random 10% subset of sites and data from 2018, suggesting a potential for predicting the distribution of the two Aedes vectors.

ecology↗

bioRxiv2018

Chikungunya virus outbreak in the Amazon region: replacement of the Asian genotype by an ECSA lineage

BackgroundSince its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.\n\nMethodology/Principal FindingsWe report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraimas state, located in the Brazilian Amazon region. In just 48 hours, we generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil.\n\nEpidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraimas population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.\n\nConclusions/SignificanceThis study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.\n\nAuthor SummaryUntil the end of 2017, Brazil notified the highest number of infections caused by chikungunya virus (CHIKV) in the Americas. We investigated a large CHIKV outbreak in Boa vista municipality in the Brazilian Amazon region. Rapid portable genome sequencing of 20 novel isolates and subsequent genetic analysis revealed that ECSA lineage was introduced from northeastern Brazil to Roraima around July 2016. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which suggests that approximately 39% of Roraimas population was infected with CHIKV-ECSA. Given the dominance of the CHIKV-Asian genotype in the Americas, our data highlights the rapid spread of a less understood and poorly characterized CHIKV-ECSA genotype in Brazil. Investigations on potential associations between public health impact of CHIKV and genetic diversity of circulating strains are warranted to better evaluate its impact in Brazil and beyond.

epidemiology↗

bioRxiv2018

Spatio-temporal dynamics of dengue in Brazil: seasonal travelling waves and determinants of regional synchrony

Dengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years.\n\nHere, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterize the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondonia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapa) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period.\n\nWe also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence.\n\nThis study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.\n\nAuthor summaryIn this paper we studied the synchronization of dengue epidemics in Brazilian regions. We found that a typical dengue season in Brazil can be described as a wave travelling from the western part of the country towards the east, with the exception of the two most northern equatorial states that experienced inconsistent seasonality of dengue epidemics.\n\nWe found that the spatial structure of dengue cases is driven by both climate and human mobility patterns. In particular, precipitation was the most important factor for the seasonality of dengue at finer spatial resolutions.\n\nOur findings increase our understanding of large scale dengue patterns and could be used to enhance national control programs against dengue and other arboviruses.

epidemiology↗

bioRxiv2018

Quantifying the impact of dengue containment activities using high-resolution observational data

Dengue virus causes over 96 million cases worldwide per year and is ex-panding rapidly in geographic range, especially in urban areas. Containment activities are an essential part of reducing the public health burden caused by dengue, but systematic evidence on the comparative efficacy of activities from the field is lacking. To our knowledge, the effect of containment activities on local (sub-city) scale disease dynamics has never been systematically characterized using empirical containment and case data. We combine data from a comprehensive dengue containment monitoring system with confirmed dengue case data from the local government hospitals to estimate the efficacy of seven common containment activities in two urban areas in Pakistan. We use a modified version of the time series Suspected Infected Recovered frame-work to estimate how the reproductive number, R0, of the outbreak changed in relation to deployment of each containment activity. We also estimate the spatial dependence of cases based on deployment of each containment activity. Both analyses suggest that activities aimed at the adult phase of the mosquito lifecycle have the highest efficacy, with fogging having the largest quantifiable effect in reducing cases immediately after deployment. In examining the efficacy of containment activities contemporaneously deployed in the same locations, results here can guide recommendations for future deployment of resources during dengue outbreaks in urban settings.

epidemiology↗

bioRxiv2018

Genomic and epidemiological monitoring of yellow fever virus transmission potential

The yellow fever virus (YFV) epidemic that began in Dec 2016 in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes sp. vectors highlights the urgent need to monitor the risk of re-establishment of domestic YFV transmission in the Americas. We use a suite of epidemiological, spatial and genomic approaches to characterize YFV transmission. We show that the age- and sex-distribution of human cases in Brazil is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally using a new protocol reveals an early phase of sylvatic YFV transmission restricted to Minas Gerais, followed in late 2016 by a rise in viral spillover to humans, and the southwards spatial expansion of the epidemic towards previously YFV-free areas. Our results establish a framework for monitoring YFV transmission in real-time, contributing to the global strategy of eliminating future yellow fever epidemics.

epidemiology↗

bioRxiv2017

Epidemic establishment and cryptic transmission of Zika virus in Brazil and the Americas

Zika virus (ZIKV) transmission in the Americas was first confirmed in May 2015 in Northeast Brazil1. Brazil has the highest number of reported ZIKV cases worldwide (>200,000 by 24 Dec 20162) as well as the greatest number of cases associated with microcephaly and other birth defects (2,366 confirmed cases by 31 Dec 20162). Following the initial detection of ZIKV in Brazil, 47 countries and territories in the Americas have reported local ZIKV transmission, with 22 of these reporting ZIKV-associated severe disease3. Yet the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of such information for interpreting past trends in reported microcephaly. To address this we generated 53 complete or partial ZIKV genomes, mostly from Brazil, including data generated by the ZiBRA project - a mobile genomics lab that travelled across Northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Joint analyses of viral genomes with ecological and epidemiological data estimate that the ZIKV epidemic first became established in NE Brazil by March 2014 and likely disseminated from there, both nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates of the international spread of ZIKV from Brazil coincide with periods of high vector suitability in recipient regions and indicate the duration of pre-detection cryptic transmission in those regions. NE Brazils role in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the virus basic reproduction number.\n\nOne Sentence SummaryVirus genomes reveal the establishment of Zika virus in Northeast Brazil and the Americas, and provide an appropriate timeframe for baseline (pre-Zika) microcephaly in different regions.

genomics↗