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Abstract BackgroundUrbanization can influence disease vectors by altering larval habitat, microclimates, and host abundance. The global increase in urbanization, especially in Africa, is likely to alter vector abundance and pathogen transmission. We investigated the effect of urbanization and weather on the abundance of two mosquitoes,Aedes aegyptiandAedes albopictus, and infection with dengue, chikungunya, and Zika viruses at 63 sites in six cities spanning a 900-km latitudinal range in Cameroon, Central Africa. MethodsWe used human landing catches and backpack-mounted aspirators to sample mosquitoes and collected larval habitat, host availability, and weather (temperature, precipitation, humidity) data for each site in each city. We analyzed land use and land cover information and satellite photos at varying radii around sites (100 m to 2 km) to quantify the extent of urbanization and the number of structures around each site. We used a continuous urbanization index (UI; range 0–100) that increased with impermeable surface and decreased with forest cover. ResultsUrbanization increased larval habitat, human host availability, andAe. aegyptimosquito abundance.Aedes aegyptiabundance increased 1.7% (95% CI 0.69–2.7%) with each 1 unit increase in the urbanization index in all six cities (Douala, Kribi, Yaounde, Ngaoundere, Garoua, and Maroua) with a 5.4-fold increase from UI = 0 to UI = 100, and also increased with rainfall. In contrast,Ae. albopictusabundance increased with urbanization in one city, but showed no influence of urbanization in two other cites. Across three cities,Ae. albopictusabundance increased with rainfall, temperature, and humidity. Finally, we did not detect Zika, dengue, or chikungunya viruses in any specimens, and found weak evidence of interspecific competition in analyses of adult population growth rates. ConclusionsThese results show that urbanization consistently increasesAe. aegyptiabundance across a broad range of habitats in Central Africa, while effects onAe. albopictuswere more variable and the abundance of both species were influenced by rainfall. Future urbanization of Africa will likely increaseAe. aegyptiabundance, and climate change will likely alter abundance of both species through changes in precipitation and temperature. Graphical Abstract 

Abstract Humans have greatly altered earth’s terrestrial water cycle with the majority of fresh water being used for agriculture. Irrigation changes spatial and temporal water availability and alters mosquito abundance and phenology. Previous studies evaluating the effect of irrigation on mosquito abundance and mosquito-borne disease have shown inconsistent results and little is known about the effect of irrigation on variability in mosquito abundance. We examined the effect of irrigation, climate and land cover on mosquito abundance and human West Nile virus (WNV) disease cases across California. Irrigation made up nearly a third of total water inputs, and exceeded precipitation in some regions. Abundance of two key vectors of several arboviruses, including WNV,Culex tarsalisand the Culex pipienscomplex, increased 17–21-fold with irrigation. Irrigation reduced seasonal variability inC. tarsalisabundance by 36.1%. Human WNV incidence increased with irrigation, which explained more than a third (34.2%) of the variation in WNV incidence among California counties. These results suggest that irrigation can increase and decouple mosquito populations from natural precipitation variability, resulting in sustained and increased disease burdens. Shifts in precipitation due to climate change are likely to result in increased irrigation in many arid regions which could increase mosquito populations and disease. 

The emergence of new virus variants, including the Omicron variant (B.1.1.529) of SARS-CoV-2, can lead to reduced vaccine effectiveness (VE) and the need for new vaccines or vaccine doses if the extent of immune evasion is severe. Neutralizing antibody titers have been shown to be a correlate of protection for SARS-CoV-2 and other pathogens, and could be used to quickly estimate vaccine effectiveness for new variants. However, no model currently exists to provide precise VE estimates for a new variant against severe disease for SARS-CoV-2 using robust datasets from several populations. We developed predictive models for VE against COVID-19 symptomatic disease and hospitalization across a 54-fold range of mean neutralizing antibody titers. For two mRNA vaccines (mRNA-1273, BNT162b2), models fit without Omicron data predicted that infection with the BA.1 Omicron variant increased the risk of hospitalization 2.8–4.4-fold and increased the risk of symptomatic disease 1.7–4.2-fold compared to the Delta variant. Out-of-sample validation showed that model predictions were accurate; all predictions were within 10% of observed VE estimates and fell within the model prediction intervals. Predictive models using neutralizing antibody titers can provide rapid VE estimates, which can inform vaccine booster timing, vaccine design, and vaccine selection for new virus variants. 

The coronavirus disease 2019 (COVID-19) pandemic challenged the workings of human society, but in doing so, it advanced our understanding of the ecology and evolution of infectious diseases. Fluctuating transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrated the highly dynamic nature of human social behavior, often without government intervention. Evolution of SARS-CoV-2 in the first two years following spillover resulted primarily in increased transmissibility, while in the third year, the globally dominant virus variants had all evolved substantial immune evasion. The combination of viral evolution and the buildup of host immunity through vaccination and infection greatly decreased the realized virulence of SARS-CoV-2 due to the age dependence of disease severity. The COVID-19 pandemic was exacerbated by presymptomatic, asymptomatic, and highly heterogeneous transmission, as well as highly variable disease severity and the broad host range of SARS-CoV-2. Insights and tools developed during the COVID-19 pandemic could provide a stronger scientific basis for preventing, mitigating, and controlling future pandemics. 

ABSTRACT Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world. 

Avian malaria is expanding upslope with warmer temperatures and driving multiple species of Hawaiian birds towards extinction. Methods to reduce malaria transmission are urgently needed to prevent further declines. ReleasingWolbachia-infected incompatible male mosquitoes could suppress mosquito populations and releasingWolbachia-infected female mosquitoes (or both sexes) could reduce pathogen transmission if theWolbachiastrain reduced vector competence. We clearedCulex quinquefasciatusof their naturalWolbachia pipientis wPip infection and transinfected them withWolbachia wAlbB isolated fromAedes albopictus. We show thatwAlbB infection was transmitted transovarially, and demonstrate cytoplasmic incompatibility with wild-type mosquitoes infected withwPip from Oahu and Maui, Hawaii. We measured vector competence for avian malaria,Plasmodium relictum, lineage GRW4, of seven mosquito lines (two withwAlbB; three with naturalwPip infection, and two cleared ofWolbachiainfection) by allowing them to feed on canaries infected with recently collected field isolates of HawaiianP.relictum. We tested 73 groups (N_total= 1176) of mosquitoes forP.relictuminfection in abdomens and thoraxes 6–14 days after feeding on a range of parasitemias from 0.028% to 2.49%, as well as a smaller subset of salivary glands. We found no measurable effect ofWolbachiaon any endpoint, but strong effects of parasitemia, days post feeding, and mosquito strain on both abdomen and thorax infection prevalence. These results suggest that releasing malewAlbB-infectedC.quinquefasciatusmosquitoes could suppresswPip-infected mosquito populations, but would have little positive or negative impact on mosquito vector competence forP.relictumifwAlbB became established in local mosquito populations. More broadly, the lack ofWolbachiaeffects on vector competence we observed highlights the variable impacts of both native and transinfectedWolbachiainfections in mosquitoes. 

Abstract Maternal age can influence reproductive success and offspring fitness, but the timing, magnitude and direction of those impacts are not well understood. Evolutionary theory predicts that selection on fertility senescence is stronger than maternal effect senescence, and therefore, the rate of maternal effect senescence will be faster than fertility senescence.We used a 36‐year study of northern elephant seals (Mirounga angustirostris) to investigate reproductive senescence. Our dataset included 103,746 sightings of 1203 known‐age female northern elephant seals.We hypothesized that fertility (maternal reproductive success), offspring survival and recruitment into the breeding population, and male offspring production would decline with advanced maternal age. Furthermore, we hypothesized that older females would shorten their moulting haul out to allow for more time spent foraging.We found evidence for both fertility and maternal effect senescence, but no evidence for senescence impacting offspring recruitment or sex ratio. Breeding probability declined from 96.4% (95% CI: 94.8%–97.5%) at 11 years old to 89.7% (81.9%–94.3%) at 19 years old, and the probability of offspring survival declined from 30.3% (23.6%–38.0%) at 11 years old to 9.1% (3.2%–22.9%) at 19 years old.The rates of decline for fertility and maternal effect senescence were not different from each other. However, maternal effect senescence had a substantially greater impact on the number of offspring surviving to age 1 compared to fertility senescence. Compared to a hypothetical non‐senescent population, maternal effect senescence resulted in 5.3% fewer surviving pups, whereas fertility senescence resulted in only 0.3% fewer pups produced per year. These results are consistent with evolutionary theory predicting weaker selection on maternal effect than fertility senescence. Maternal effect senescence may therefore be more influential on population dynamics than fertility senescence in some systems. 

The ongoing COVID-19 pandemic has killed at least 1.1 million people in the United States and over 6.7 million globally. Accurately estimating the age-specific infection fatality rate (IFR) of SARS-CoV-2 for different populations is crucial for assessing and understanding the impact of COVID-19 and for appropriately allocating vaccines and treatments to at-risk groups. We estimated age-specific IFRs of wild-type SARS-CoV-2 using published seroprevalence, case, and death data from New York City (NYC) from March to May 2020, using a Bayesian framework that accounted for delays between key epidemiological events. IFRs increased 3-4-fold with every 20 years of age, from 0.06% in individuals between 18–45 years old to 4.7% in individuals over 75. We then compared IFRs in NYC to several city- and country-wide estimates including England, Switzerland (Geneva), Sweden (Stockholm), Belgium, Mexico, and Brazil, as well as a global estimate. IFRs in NYC were higher for individuals younger than 65 years old than most other populations, but similar for older individuals. IFRs for age groups less than 65 decreased with income and increased with income inequality measured using the Gini index. These results demonstrate that the age-specific fatality of COVID-19 differs among developed countries and raises questions about factors underlying these differences, including underlying health conditions and healthcare access.