Biology subjects

Salje, H.

Publications and source records attributed to Salje, H..

15 recordsLinked to original sources

bioRxiv2026

Exploring the diversity and spatial distribution of Anopheles mosquitoes and their associated Plasmodium species in Tanzania using the ANOSPP amplicon panel

Species-level identification of malaria vectors and parasites is essential for targeted vector control, surveillance, and clinical case management. However, routine surveillance often relies on morphology, species group-restricted PCR assays, and parasite-detection workflows optimised for Plasmodium falciparum, potentially masking wider vector and parasite diversity. To address this gap, we applied the previously published ANOSPP amplicon sequencing panel to Anopheles mosquitoes collected across 25 districts in mainland Tanzania between 2020 and 2023, using it to characterise vector and parasite diversity, evaluate routine species assignments, and examine how primary-vector occurrence related to national malaria endemicity patterns. Of 71,146 mosquitoes collected, 10,020 were morphologically identified as Anopheles. ANOSPP-based identification resolved 15 Anopheles taxa, including the first Tanzanian record of Anopheles funestus-like mosquitoes (n = 10) and the first resolution of Anopheles longipalpis to Type C in the country (n = 13). Using ANOSPP as the reference, morphology misclassified 6.2% of ANOSPP-analysed specimens, with Anopheles rufipes and Anopheles maculipalpis frequently misclassified, and Anopheles pretoriensis and Anopheles marshallii sensu lato completely missed. Five Plasmodium species were detected across 37 parasite-positive mosquitoes: P. falciparum, P. vivax, P. ovale, P. malariae, and P. caprae. Plasmodium caprae was detected only in Anopheles arabiensis (n = 6), representing the first record of this parasite in Tanzania and its first detection in An. arabiensis globally. Co-occurrence of An. arabiensis, An. funestus s.s., and An. gambiae s.s. was more common in higher malaria transmission strata, whereas occurrence of An. arabiensis alone predominated in very-low and low strata. These findings show that integrating ANOSPP into surveillance can substantially improve vector and parasite resolution, uncover overlooked diversity, and strengthen species-informed malaria surveillance. Author summaryEffective malaria control requires accurate data on mosquito species distributions and the parasites they carry. However, in many settings surveillance still relies mainly on morphological identification or molecular tests targeting limited vector groups, while parasite detection often focuses on Plasmodium falciparum. This limits understanding of mosquito and parasite diversity, obscuring transmission dynamics. We used the previously published ANOSPP amplicon panel to analyse Anopheles mosquitoes across Tanzania. This revealed hidden biological complexity with direct implications for malaria transmission, resolving 15 mosquito and five Plasmodium species. Notably, for the first time in Tanzania, we detected the goat-associated parasite Plasmodium caprae in Anopheles arabiensis and identified An. funestus-like, whose vectorial capacity remains unclear, and An. longipalpis Type C, implicated in malaria transmission in dryland Kenya. Interestingly, co-occurrence of all three major Tanzanian vectors aligned with higher transmission settings, whereas areas where An. arabiensis was the sole vector were mainly in lower transmission settings. These findings show that species-resolved surveillance can reveal hidden biological complexity and provide a stronger basis for locally targeted malaria control.

genomics↗

bioRxiv2025

Heterogeneity in inhibition of genetically diverse dengue virus strains by Wolbachia

The release of Aedes aegypti mosquitoes transinfected with the virus-inhibiting Wolbachia bacterium has the potential to reduce the burden caused by dengue virus (DENV). However, the robustness of this control strategy across the wide genetic diversity of DENV remains unknown. Here, we systematically tested two commonly used Wolbachia strains (wAlbB and wMelM) for their ability to inhibit 60 genetically diverse DENV isolates spanning all four serotypes. We found stronger inhibition by wMelM (median relative dissemination: 0.04) than wAlbB (median relative dissemination: 0.19). Furthermore, while we found substantial heterogeneity in inhibition across DENV isolates, we found that more DENV-3 isolates were weakly inhibited (median relative dissemination: 0.47 for wAlbB and 0.39 for wMelM) compared to the other serotypes (median relative disseminations: 0.10-0.18 for wAlbB and 0-0.11 for wMelM). Using transmission dynamic models, we further showed that differential Wolbachia inhibition results in increased probability of reemergence, particularly in high transmission intensity settings, with strong selection for DENV strains that have higher relative dissemination in mosquitoes. Our work highlights the importance of considering DENV genetic diversity, including the long-term risk of selection, in Wolbachia-based control interventions.

microbiology↗

bioRxiv2025

Mapping antigenic evolution of influenza A virus using deep learning-based prediction of hemagglutination inhibition titers

Seasonal influenza remains a significant public health challenge through unpredictable antigenic drift, where accumulated mutations enable immune evasion and necessitate vaccine updates. Comprehensive antigenic characterization has been hindered by the absence of real-world A(H1N1)pdm antigenic mapping and post-2012 A(H3N2) maps due to insufficient pair-wise hemagglutination inhibition (HAI) titrations. Here, we present an end-to-end transformer model that predicts HAI titers directly from viral genetic sequences with error under two-fold, comparable to experimental variability. This approach enables rapid and high-throughput augmentation of HAI titrations across viral isolates, allowing for constructing large-scale antigenic maps. Several novel evolutionary patterns emerged from our analysis. Our antigenic mapping identified three A(H3N2) clusters between 2012-2022 with transitions occurring approximately every 6 years. Notably, genetically diverse co-circulating subclades 3C.2a and 3C.3a (2015-2020) formed a single antigenic cluster. A(H1N1)pdm formed three less temporally distinct clusters, with a novel cluster emerging post-COVID-19. Using interpretable analysis, we identified mutation sites linked to antigenic cluster transitions that align with previous laboratory findings. Key A(H3N2) mutations primarily occurred within major antigenic epitopes, while A(H1N1) showed fewer key mutations, some outside recognized antigenic regions. Our deep learning approach accelerates antigenic characterization in surveillance at global scale and can be transferred to other variable pathogens, providing an actionable bridge between genomic sequencing and vaccine strain selection.

evolutionary biology↗

bioRxiv2023

Geographic migration and vaccine-induced fitness changes of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location. The extent and mechanisms of spread, and vaccine-driven changes in fitness and antimicrobial resistance (AMR), remain largely unquantified. Using geolocated genome sequences from South Africa (N=6910, 2000-2014) we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately we estimated the population level changes in fitness of strains that are (vaccine type, VT) and are not (non-vaccine type, NVT) included in the vaccine, first implemented in 2009, as well as differences in strain fitness between those that are and are not resistant to penicillin. We estimated that pneumococci only become homogenously mixed across South Africa after about 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Further, in the years following vaccine implementation the relative fitness of NVT compared to VT strains increased (RR: 1.29 [95% CI 1.20-1.37]) - with an increasing proportion of these NVT strains becoming penicillin resistant. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in AMR may be transient. One-Sentence SummaryWe describe geographic migration, and fitness dynamics conferred by NVT strains and AMR, for the globally endemic pathogen Streptococcus pneumoniae.

evolutionary biology↗

bioRxiv2021

Spatial dynamics and vaccine-induced fitness changes of Bordetella pertussis

Competitive interactions between pathogen strains drive infection risk. Vaccines are thought to perturb strain diversity through shifts in immune pressures, however, this has rarely been measured due to inadequate data and analytical tools. Bordetella pertussis (B. pertussis), responsible for 160,000 deaths annually1, provides a rare natural experiment as many countries have switched from whole cell vaccines to acellular vaccines, which have very different immunogenic properties2,3. Here we use 3,344 sequences from 23 countries and build phylogenetic models to reveal that B. pertussis has substantial diversity within communities, with the relative fitness of local genotypes changing in response to switches in vaccine policy. We demonstrate that the number of transmission chains circulating within subnational regions is strongly associated with host population size. It takes 5-10 years for individual lineages to be homogeneously distributed throughout Europe or the United States. Increased fitness of pertactin-deficient strains following implementation of acellular vaccines, but reduced fitness otherwise, can explain long-term genotype dynamics. These findings highlight the role of national vaccine policies in shifting local diversity of a pathogen that still poses a large burden on global public health.

genetics↗

bioRxiv2021

How do I bite thee? Let me count the ways: Heterogeneity and temperature dependence in Ae. aegypti biting habits drive individual mosquito arbovirus transmission potential

In models of mosquito-borne transmission, the mosquito biting rate is an influential parameter, and understanding the heterogeneity of the process of biting is important, as biting is usually assumed to be relatively homogeneous across individuals, with time-between-bites described by an exponentially distributed process. However, these assumptions have not been addressed through laboratory experimentation. We experimentally investigated the daily biting habits of Ae. aegypti at three temperatures (24{degrees}C, 28{degrees}C, and 32{degrees}C) and determined that there was individual heterogeneity in biting habits (number of bites, timing of bites, etc.). We further explored the consequences of biting heterogeneity using an individual-based model designed to examine whether a particular biting profile determines whether a mosquito is more or less likely to 1) become exposed given a single index case of dengue (DENV) and 2) transmit to a susceptible human individual. Our experimental results indicate that there is heterogeneity among individuals and among temperature treatments. We further show that this results in altered probabilities of transmission of DENV to and from individual mosquitoes based on biting profiles. While current model representation of biting may work under some conditions, it might not uniformly be the best fit for this process. Our data also confirm that biting is a non-monotonic process with temperatures around 28{degrees}C being optimum. Author SummaryMosquito biting is a necessary and critical part of arbovirus transmission. The mosquito must bite once to acquire a virus and again to transmit, and these two bites must be separated by sufficient time for the virus to get to the salivary glands of the mosquito. Thus, both the number and timing of bites is important. We experimentally investigated how these bite characteristics might be different among individuals and further explored how temperature affected the overall heterogeneity of biting in Aedes aegypti mosquitoes, which carry many arboviruses like dengue virus (DENV). We found that the biting profiles - including number and timing thereof - did vary within temperature groups among individuals and compared outcomes associated with each individual in an individual based model of household DENV transmission. Our results further confirmed that temperatures around 28{degrees}C are optimal for mosquito biting (and transmission), that correlations between biting characteristics and transmission were not uniform across temperature, which represents another layer of heterogeneity, and that - at least at 28{degrees}C - the null assumption of an exponential or an exponential like (geometric) distribution of biting in mathematical models of transmission is not the best and offer an alternative.

ecology↗

bioRxiv2021

Periodic synchronization of dengue epidemics in Thailand: the roles played by temperature and immunity

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, the largest impacts of climate change on dengue might be in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatio-temporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last thirty years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronization events. We show that patterns in synchrony of dengue are consistent with those observed in temperature. Applying a temperature-driven dengue model, we explore how dynamics of immunity interact with temperature to produce the observed multiannual dynamics and patterns in synchrony. While multiannual oscillations are readily produced by immunity in absence of multiannual timescales in temperature, synchrony in temperature can synchronise dengue dynamics in different locations. However, at higher mean temperatures and lower seasonal variation, immune dynamics become more predominant, and dengue dynamics become more insensitive to multiannual fluctuations in temperature. These findings can help underpin predictions of disease patterns as global temperatures rise. Author summary

ecology↗

bioRxiv2020

Emergence and global spread of Listeria monocytogenes main clinical clonal complex

Retracing microbial emergence and spread is essential to understanding the evolution and dynamics of pathogens. The bacterial foodborne pathogen Listeria monocytogenes clonal complex 1 (Lm-CC1) is the most prevalent clonal group associated with listeriosis, and is strongly associated with cattle and dairy products. Here we analysed 2,021 Lm-CC1 isolates collected from 40 countries, since the first Lm isolation to the present day, to define its evolutionary history and population dynamics. Our results suggest that Lm-CC1 spread worldwide from North America following the Industrial Revolution through two waves of expansion, coinciding with the transatlantic livestock trade in the second half of the 19th century and the rapid growth of cattle farming in the 20th century. Lm-CC1 then firmly established at a local level, with limited inter-country spread. This study provides an unprecedented insight into Lm-CC1 phylogeography and dynamics and can contribute to effective disease surveillance to reduce the burden of listeriosis.

genomics↗

bioRxiv2020

The ecology of Nipah virus in Bangladesh: a nexus of land use change and opportunistic feeding behavior in bats

Nipah virus is a bat-borne paramyxovirus that produces yearly outbreaks of fatal encephalitis in Bangladesh. Understanding the ecological conditions that lead to spillover from bats to humans can assist in designing effective interventions. To investigate the current and historical processes that drive Nipah spillover in Bangladesh, we analyzed the relationship between spillover events and climatic conditions, the spatial distribution and size of Pteropus medius roosts, and patterns of land use change in Bangladesh over the last 300 years. We found that 53% of annual variation in winter spillovers is explained by winter temperature, which may affect bat behavior, physiology, and human risk behaviors. We infer from changes in forest cover that a progressive shift in bat roosting behavior occurred over hundreds of years, producing the current system where a majority of P. medius populations are small (median of 150 bats), occupy roost sites for 10 years or more, live in areas of high human population density, and opportunistically feed on cultivated food resources - conditions that promote viral spillover. Without interventions, continuing anthropogenic pressure on bat populations similar to what has occurred in Bangladesh could result in more regular spillovers of other bat viruses, including Hendra and Ebola viruses.

ecology↗

bioRxiv2019

Opportunities for improved surveillance and control of infectious diseases from age-specific case data

One of the challenges faced by global disease surveillance efforts is the lack of comparability across systems. Reporting commonly focuses on overall incidence, despite differences in surveillance quality between and within countries. For most immunizing infections, the age-distribution of incident cases provides a more robust picture of trends in transmission. We present a framework to estimate transmission intensity for dengue virus from age-specific incidence data, and apply it to 363 administrative units in Thailand, Colombia, Brazil and Mexico. Our estimates correlate well with those derived from seroprevalence data (the gold-standard), capture the expected spatial heterogeneity in risk, and correlate with known environmental drivers of transmission. We show how this approach could be used to guide the implementation of control strategies such as vaccination. Since age-specific counts are routinely collected by many surveillance systems, they represent a unique opportunity to further our understanding of disease burden and risk for many diseases.

epidemiology↗

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

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

Differential human mobility and local variation in human infection attack rate

Infectious disease transmission in animals is an inherently spatial process in which a hosts home location and their social mixing patterns are important, with the mixing of infectious individuals often different to that of susceptible individuals. Although incidence data for humans have traditionally been aggregated into low-resolution data sets, modern representative surveillance systems such as electronic hospital records generate high volume case data with precise home locations. Here, we use a high resolution gridded spatial transmission model of arbitrary resolution to investigate the theoretical relationship between population density, differential population movement and local variability in incidence. We show analytically that uniform local attack rate is only possible for individual pixels in the grid if susceptible and infectious individuals move in the same way. Using a population in Guangdong, China, for which a robust quantitative description of movement is available (a movement kernel), and a natural history consistent with pandemic influenza; we show that for the estimated kernel, local cumulative incidence is positively correlated with population density when susceptible individuals are more connected in space than infectious individuals. Conversely, when infectious individuals are more connected, local cumulative incidence is negatively correlated with population density. The amplitude of correlation is substantial for the estimated kernel. However, the strength and direction of correlation changes sign for other kernel parameter values. These results describe a precise relationship between the spatio-social mixing of infectious and susceptible individuals and local variability in attack rates, and suggest a plausible mechanism for the counter-intuitive scenario in which local incidence is lower on average in less dense populations. Also, these results suggest that if spatial transmission models are implemented at high resolution to investigate local disease dynamics, including micro-tuning of interventions, the underlying detailed assumptions about the mechanisms of transmission become more important than when similar studies are conducted at larger spatial scales.\n\nAuthor SummaryWe know that some places have higher rates of infectious disease than others. However, at the moment, we usually only measure these differences for large towns and cities. With modern data, such as those we can get from mobile phones, we can measure rates of infection at much smaller scales. In this paper, we used a computer simulation of an epidemic to propose ways that rates of incidence in small local areas might be related to population density. We found that if infectious people are better connected than non-infectious people, perhaps because they receive visitors, then, on average, higher density areas would have lower rates of infection. If infectious people were less connected than non-infectious people then higher density areas would have higher rates of infection. As data get more accurate, this type of analysis will allow us to propose and test ways to optimize interventions such as the delivery of vaccines and antivirals during a pandemic.

epidemiology↗

bioRxiv2018

Micro-hotspots of Risk in Urban Cholera Epidemics

Targeted interventions have been delivered to neighbors of cholera cases in epidemic responses in Haiti and Africa despite little evidence supporting impact. Using data from urban epidemics in Chad and D.R. Congo we estimate the size and extent of spatiotemporal zones of increased cholera risk around cases. In both cities, we found zones of increased risk of at least 200-meters during the 5-days immediately following case presentation to a clinic. Risk was highest for those living closest to cases and diminished in time and space similarly across settings. These results provide a rational basis for targeting interventions, if delivered rapidly.

epidemiology↗