Rapid mechanosensitive migration and dispersal of newly divided mesenchymal cells aid their recruitment into dermal condensates.

Embryonic mesenchymal cells are dispersed within an extracellular matrix but can coalesce to form condensates with key developmental roles. Cells within condensates undergo fate and morphological changes and induce cell fate changes in nearby epithelia to produce structures including hair follicles, feathers, or intestinal villi. Here, by imaging mouse and chicken embryonic skin, we find that mesenchymal cells undergo much of their dispersal in early interphase, in a stereotyped process of displacement driven by 3 hours of rapid and persistent migration followed by a long period of low motility. The cell division plane and the elevated migration speed and persistence of newly born mesenchymal cells are mechanosensitive, aligning with tissue tension, and are reliant on active WNT secretion. This behaviour disperses mesenchymal cells and allows daughters of recent divisions to travel long distances to enter dermal condensates, demonstrating an unanticipated effect of cell cycle subphase on core mesenchymal behaviour.

Hotspots and super-spreaders: Modelling fine-scale malaria parasite transmission using mosquito flight behaviour.

Malaria hotspots have been the focus of public health managers for several years due to the potential elimination gains that can be obtained from targeting them. The identification of hotspots must be accompanied by the description of the overall network of stable and unstable hotspots of malaria, especially in medium and low transmission settings where malaria elimination is targeted. Targeting hotspots with malaria control interventions has, so far, not produced expected benefits. In this work we have employed a mechanistic-stochastic algorithm to identify clusters of super-spreader houses and their related stable hotspots by accounting for mosquito flight capabilities and the spatial configuration of malaria infections at the house level. Our results show that the number of super-spreading houses and hotspots is dependent on the spatial configuration of the villages. In addition, super-spreaders are also associated to house characteristics such as livestock and family composition. We found that most of the transmission is associated with winds between 6pm and 10pm although later hours are also important. Mixed mosquito flight (downwind and upwind both with random components) were the most likely movements causing the spread of malaria in two out of the three study areas. Finally, our algorithm (named MALSWOTS) provided an estimate of the speed of malaria infection progression from house to house which was around 200-400 meters per day, a figure coherent with mark-release-recapture studies of Anopheles dispersion. Cross validation using an out-of-sample procedure showed accurate identification of hotspots. Our findings provide a significant contribution towards the identification and development of optimal tools for efficient and effective spatio-temporal targeted malaria interventions over potential hotspot areas.

Unravelling the impact of insecticide-treated bed nets on childhood malaria in Malawi.

BACKGROUND: To achieve malaria elimination it is essential to understand the impact of insecticide-treated net (ITNs) programmes. Here, the impact of ITN access and use on malaria prevalence in children in Malawi was investigated using Malaria Indicator Survey (MIS) data. METHODS: MIS data from 2012, 2014 and 2017 were used to investigate the relationship between malaria prevalence in children (6-59 months) and ITN use. Generalized linear modelling (GLM), geostatistical mixed regression modelling and non-stationary GLM were undertaken to evaluate trends, spatial patterns and local dynamics, respectively. RESULTS: Malaria prevalence in Malawi was 27.1% (95% CI 23.1-31.2%) in 2012 and similar in both 2014 (32.1%, 95% CI 25.5-38.7) and 2017 (23.9%, 95% CI 20.3-27.4%). ITN coverage and use increased during the same time period, with household ITN access growing from 19.0% (95% CI 15.6-22.3%) of households with at least 1 ITN for every 2 people sleeping in the house the night before to 41.7% (95% CI 39.1-44.4%) and ITN use from 41.1% (95% CI 37.3-44.9%) of the population sleeping under an ITN the previous night to 57.4% (95% CI 55.0-59.9%). Both the geostatistical and non-stationary GLM regression models showed child malaria prevalence had a negative association with ITN population access and a positive association with ITN use although affected by large uncertainties. The non-stationary GLM highlighted the spatital heterogeneity in the relationship between childhood malaria and ITN dynamics across the country. CONCLUSION: Malaria prevalence in children under five had a negative association with ITN population access and a positive association with ITN use, with spatial heterogeneity in these relationships across Malawi. This study presents an important modelling approach that allows malaria control programmes to spatially disentangle the impact of interventions on malaria cases.

Education and Socio-economic status are key factors influencing use of insecticides and malaria knowledge in rural farmers in Southern Côte d'Ivoire.

BACKGROUND: Insecticides play a key role in rural farming; however, their over- or misuse has been linked with a negative impact on malaria vector control policies. This study was conducted amongst agricultural communities in Southern Côte d'Ivoire to identify which insecticides are used by local farmers and how it relates to the perception of farmers on malaria. Understanding the use of insecticides may help in designing awareness programme on mosquito control and pesticides management. METHODS: A questionnaire was administered to 1399 farming households across ten villages. Farmers were interviewed on their education, farming practices (e.g. crops cultivated, insecticides use), perception of malaria, and the different domestic strategies of mosquito control they use. Based on some pre-defined household assets, the socioeconomic status (SES) of each household was estimated. Statistical associations were calculated between different variables, showing significant risk factors. RESULTS: The educational level of farmers was significantly associated with their SES (p < 0.0001). Most of the householders (88.82%) identified mosquitoes as the principal cause of malaria, with good knowledge of malaria resulting as positively related to high educational level (OR = 2.04; 95%CI: 1.35, 3.10). The use of indoor chemical compounds was strongly associated to the SES of the households, their education level, their use of ITNs and insecticide in agricultural (p < 0.0001). Indoor application of pyrethroid insecticides was found to be widespread among farmers as well as the use of such insecticide for crops protection. CONCLUSION: Our study shows that the education level remains the key factor influencing the use of insecticides by farmers and their awareness of malaria control. We suggest that better communication tailored to education level and including SES, controlled availability and access to chemical products, should be considered when designing campaigns on use of pesticides and vector borne disease control for local communities.

A geostatistical analysis of the association between armed conflicts and Plasmodium falciparum malaria in Africa, 1997-2010.

BACKGROUND: The absence of conflict in a country has been cited as a crucial factor affecting the operational feasibility of achieving malaria control and elimination, yet mixed evidence exists on the influence that conflicts have had on malaria transmission. Over the past two decades, Africa has seen substantial numbers of armed conflicts of varying length and scale, creating conditions that can disrupt control efforts and impact malaria transmission. However, very few studies have quantitatively assessed the associations between conflicts and malaria transmission, particularly in a consistent way across multiple countries. METHODS: In this analysis an explicit geostatistical, autoregressive, mixed model is employed to quantitatively assess the association between conflicts and variations in Plasmodium falciparum parasite prevalence across a 13-year period in sub-Saharan Africa. RESULTS: Analyses of geolocated, malaria prevalence survey variations against armed conflict data in general showed a wide, but short-lived impact of conflict events geographically. The number of countries with decreased P. falciparum parasite prevalence (17) is larger than the number of countries with increased transmission (12), and notably, some of the countries with the highest transmission pre-conflict were still found with lower transmission post-conflict. For four countries, there were no significant changes in parasite prevalence. Finally, distance from conflicts, duration of conflicts, violence of conflict, and number of conflicts were significant components in the model explaining the changes in P. falciparum parasite rate. CONCLUSIONS: The results suggest that the maintenance of intervention coverage and provision of healthcare in conflict situations to protect vulnerable populations can maintain gains in even the most difficult of circumstances, and that conflict does not represent a substantial barrier to elimination goals.

Length of stay and economic sustainability of virtual ward care in a medium-sized hospital of the UK: a retrospective longitudinal study.

OBJECTIVE: To evaluate the length of stay difference and its economic implications between hospital patients and virtual ward patients. DESIGN: Retrospective longitudinal study. SETTING: Wrightington, Wigan and Leigh (WWL) Teaching Hospitals, National Health Service (NHS) Foundation Trust, a medium-sized NHS trust in the north-west of England. PARTICIPANTS: Virtual ward patients (n=318) were matched 1:1 to 1:4, depending on matching characteristics, to all hospital patients (n=350). All patients were admitted to the hospital during the calendar year 2022. OUTCOME MEASURES: The primary outcome is the length of stay as defined from the date of hospital admission to the date of discharge or death (hospital patients) and from the date of hospital admission to the date of admission in a virtual ward (virtual ward patients). The secondary outcome is the cost of a hospital bed day and the equivalent value of virtual ward savings in hospital bed days. Additional measures were 6-month readmission rates and survival rates at the follow-up date of 30 April 2023. RISK FACTORS: Age, sex, comorbidities and the clinical frailty score (CFS) were used to evaluate the importance and effect of these factors on the main and secondary outcomes. METHODS: Statistical analyses included logistic and binomial mixed models for the length of stay in the hospital and readmission rate outcomes, as well as a Cox proportional hazard model for the survival of the patients. RESULTS: The virtual ward patients had a shorter stay in the hospital before being admitted to the virtual ward (2.89 days, 95% CI 2.1 to 3.9 days). Chronic kidney disease (CKD) and frailty were associated with a longer length of stay in the hospital (58%, 95% CI 22% to 100%) compared with patients without CKD, and 14% (95% CI 8% to 21%) compared with patients with one unit lower CFS. The frailty score was also associated with a higher rate of readmission within 6 months and lower survival. Being admitted to the virtual ward slightly improved survival, although when readmitted, survival deteriorated rapidly. The cost of a 24-hour period in a general hospital bed is £536. The cost of a day hospital saved by a virtual ward was £935. CONCLUSION: The use of a 40-bed virtual ward was clinically effective in terms of survival for patients not needing readmission and allowed for the freeing of three hospital beds per day. However, the cost for each day freed from hospital stay was three-quarters larger than the one for a single-day hospital bed. This raises concerns about the deployment of large-scale virtual wards without the existence of policies and plans for their cost-effective management.

Determining the distance patterns in the movements of future doctors in UK between 2002 and 2015: a retrospective cohort study.

OBJECTIVE: To determine and identify distance patterns in the movements of medical students and junior doctors between their training locations. DESIGN: A retrospective cohort study of UK medical students from 2002 to 2015 (UKMED data). SETTING: All UK medical schools, foundations and specialty training organisation. PARTICIPANTS: All UK medical students from 2002 to 2015, for a total of 97 932 participants. OUTCOME MEASURES: Individual movements and number of movements by county of students from family home to medical school training, from medical school to foundation training and from foundation to specialty training. METHODS: Leslie matrix, principal components analysis, Gini coefficient, χ2 test, generalised linear models and variable selection methods were employed to explore the different facets of students' and junior doctors' movements from the family home to medical school and for the full pathway (from family home to specialty training). RESULTS: The majority of the movements between the different stages of the full pathway were restricted to a distance of up to 50 km; although the proportion of movements changed from year-to-year, with longer movements during 2007-2008. At the individual level, ethnicity, socioeconomic class of the parent(s) and the deprivation score of the family home region were found to be the most important factors associated with the length of the movements from the family home to medical school. Similar results were found when movements were aggregated at the county level, with the addition of factors such as gender and qualification at entry (to medical school) being statistically associated with the number of new entrant students moving between counties. CONCLUSION: Our findings show that while future doctors do not move far from their family home or training location, this pattern is not homogeneous over time. Distances are influenced by demographics, socioeconomic status and deprivation. These results may contribute in designing interventions aimed at solving the chronic problems of maldistribution and underdoctoring in the UK.

Spatiotemporal distribution and bionomics of Anopheles stephensi in different eco-epidemiological settings in Ethiopia.

BACKGROUND: Malaria is a major public health concern in Ethiopia, and its incidence could worsen with the spread of the invasive mosquito species Anopheles stephensi in the country. This study aimed to provide updates on the distribution of An. stephensi and likely household exposure in Ethiopia. METHODS: Entomological surveillance was performed in 26 urban settings in Ethiopia from 2021 to 2023. A kilometer-by-kilometer quadrant was established per town, and approximately 20 structures per quadrant were surveyed every 3 months. Additional extensive sampling was conducted in 50 randomly selected structures in four urban centers in 2022 and 2023 to assess households' exposure to An. stephensi. Prokopack aspirators and CDC light traps were used to collect adult mosquitoes, and standard dippers were used to collect immature stages. The collected mosquitoes were identified to species level by morphological keys and molecular methods. PCR assays were used to assess Plasmodium infection and mosquito blood meal source. RESULTS: Catches of adult An. stephensi were generally low (mean: 0.15 per trap), with eight positive sites among the 26 surveyed. This mosquito species was reported for the first time in Assosa, western Ethiopia. Anopheles stephensi was the predominant species in four of the eight positive sites, accounting for 75-100% relative abundance of the adult Anopheles catches. Household-level exposure, defined as the percentage of households with a peridomestic presence of An. stephensi, ranged from 18% in Metehara to 30% in Danan. Anopheles arabiensis was the predominant species in 20 of the 26 sites, accounting for 42.9-100% of the Anopheles catches. Bovine blood index, ovine blood index and human blood index values were 69.2%, 32.3% and 24.6%, respectively, for An. stephensi, and 65.4%, 46.7% and 35.8%, respectively, for An. arabiensis. None of the 197 An. stephensi mosquitoes assayed tested positive for Plasmodium sporozoite, while of the 1434 An. arabiensis mosquitoes assayed, 62 were positive for Plasmodium (10 for P. falciparum and 52 for P. vivax). CONCLUSIONS: This study shows that the geographical range of An. stephensi has expanded to western Ethiopia. Strongly zoophagic behavior coupled with low adult catches might explain the absence of Plasmodium infection. The level of household exposure to An. stephensi in this study varied across positive sites. Further research is needed to better understand the bionomics and contribution of An. stephensi to malaria transmission.

Food insecurity, mental health and in-hospital mortality following the COVID-19 pandemic in a socially deprived UK coastal town.

Background: Public health interventions are essential to prevent a long tail of costly, avoidable and worsening ill health in coastal communities following the COVID-19 pandemic, yet no research exists to guide policy and practice as to which groups within coastal communities are vulnerable and most in need of such interventions. Within this aim, we explore engrained and emerging vulnerabilities of food insecurity, health and well-being for different demographic groups within the deprived coastal community of Fleetwood, Lancashire, UK, before and after the pandemic. Methods: Routinely collected data of free school meal eligibility, community mental health referrals and hospital admissions between 28 March 2016 and 31 December 2021 were aggregated by locality and deprivation within Fleetwood. Temporal autoregressive models, generalised linear mixed models and survival analyses were employed to compare trends and associations in food insecurity, health and well-being indicators against deprivation indices, demographics, comorbidities (including COVID-19), the COVID-19 pandemic period and locality. Results: Areas with better housing and income, but higher health and disability deprivation, showed increased levels of free school meal eligibility following the pandemic. Mental health was insensitive to the first 14 months of pandemic yet is worsened by unemployment deprivation and cardiovascular and respiratory comorbidities, with a greater predisposition to poor mental health in adolescents and young adults. After accounting for the effect of COVID-19, hospital mortality risk increased with demographic influences in fitting with the typology of coastal communities having an older population, struggling healthcare and a greater prevalence of comorbidities. Conclusions: Public health managers and policy makers seeking to prevent worsening health and well-being within coastal communities following the pandemic should focus on broader-scale patterns reflecting entrenched poor health typical of coastal communities, and emerging food insecurity within specific demographic and deprivation groups at finer scales.

Autism trends in a medium size coastal town of England.

Autism spectrum disorder (ASD) is a complex set of neurodevelopmental conditions which affects just under 1% of the global population. This study aims to investigate the trends in ASD diagnoses in a typical English deprived coastal community over the last two decades. ASD information for patients registered at Fleetwood GP practices were provided for the period between July 1952 to March 2022. The incidence and prevalence were calculated and Poisson regression modelling was employed to estimate the effects of age and sex on the number of ASD diagnoses over time. The study shows that there has been an upward trend in the number of ASD diagnoses over the past two decades. Model's results showed that sex differences in ASD diagnoses are less pronounced when accounting for time trends. The study findings show that Fleetwood has experienced a similar rise in ASD cases as the rest of the UK, most likely due to increased awareness that may explain the time effects over gender differences. However, due to the small sample size of the study, confirmation of the gender results and identification of the factors determining the temporal trends are needed in order to determine the gender effects in ASD diagnosis.

Evidence for a role of Anopheles stephensi in the spread of drug- and diagnosis-resistant malaria in Africa.

Anopheles stephensi, an Asian malaria vector, continues to expand across Africa. The vector is now firmly established in urban settings in the Horn of Africa. Its presence in areas where malaria resurged suggested a possible role in causing malaria outbreaks. Here, using a prospective case-control design, we investigated the role of An. stephensi in transmission following a malaria outbreak in Dire Dawa, Ethiopia in April-July 2022. Screening contacts of patients with malaria and febrile controls revealed spatial clustering of Plasmodium falciparum infections around patients with malaria in strong association with the presence of An. stephensi in the household vicinity. Plasmodium sporozoites were detected in these mosquitoes. This outbreak involved clonal propagation of parasites with molecular signatures of artemisinin and diagnostic resistance. To our knowledge, this study provides the strongest evidence so far for a role of An. stephensi in driving an urban malaria outbreak in Africa, highlighting the major public health threat posed by this fast-spreading mosquito.

Mosquito vector competence for dengue is modulated by insect-specific viruses.

Aedes aegypti and A. albopictus mosquitoes are the main vectors for dengue virus (DENV) and other arboviruses, including Zika virus (ZIKV). Understanding the factors that affect transmission of arboviruses from mosquitoes to humans is a priority because it could inform public health and targeted interventions. Reasoning that interactions among viruses in the vector insect might affect transmission, we analysed the viromes of 815 urban Aedes mosquitoes collected from 12 countries worldwide. Two mosquito-specific viruses, Phasi Charoen-like virus (PCLV) and Humaita Tubiacanga virus (HTV), were the most abundant in A. aegypti worldwide. Spatiotemporal analyses of virus circulation in an endemic urban area revealed a 200% increase in chances of having DENV in wild A. aegypti mosquitoes when both HTV and PCLV were present. Using a mouse model in the laboratory, we showed that the presence of HTV and PCLV increased the ability of mosquitoes to transmit DENV and ZIKV to a vertebrate host. By transcriptomic analysis, we found that in DENV-infected mosquitoes, HTV and PCLV block the downregulation of histone H4, which we identify as an important proviral host factor in vivo.

A new algorithm quantifies the roles of wind and midge flight activity in the bluetongue epizootic in northwest Europe.

The 2006 bluetongue (BT) outbreak in northwestern Europe had devastating effects on cattle and sheep in that intensively farmed area. The role of wind in disease spread, through its effect on Culicoides dispersal, is still uncertain, and remains unquantified. We examine here the relationship between farm-level infection dates and wind speed and direction within the framework of a novel model involving both mechanistic and stochastic steps. We consider wind as both a carrier of host semio-chemicals, to which midges might respond by upwind flight, and as a transporter of the midges themselves, in a more or less downwind direction. For completeness, we also consider midge movement independent of wind and various combinations of upwind, downwind and random movements. Using stochastic simulation, we are able to explain infection onset at 94 per cent of the 2025 affected farms. We conclude that 54 per cent of outbreaks occurred through (presumably midge) movement of infections over distances of no more than 5 km, 92 per cent over distances of no more than 31 km and only 2 per cent over any greater distances. The modal value for all infections combined is less than 1 km. Our analysis suggests that previous claims for a higher frequency of long-distance infections are unfounded. We suggest that many apparent long-distance infections resulted from sequences of shorter-range infections; a 'stepping stone' effect. Our analysis also found that downwind movement (the only sort so far considered in explanations of BT epidemics) is responsible for only 39 per cent of all infections, and highlights the effective contribution to disease spread of upwind midge movement, which accounted for 38 per cent of all infections. The importance of midge flight speed is also investigated. Within the same model framework, lower midge active flight speed (of 0.13 rather than 0.5 m s(-1)) reduced virtually to zero the role of upwind movement, mainly because modelled wind speeds in the area concerned were usually greater than such flight speed. Our analysis, therefore, highlights the need to improve our knowledge of midge flight speed in field situations, which is still very poorly understood. Finally, the model returned an intrinsic incubation period of 8 days, in accordance with the values reported in the literature. We argue that better understanding of the movement of infected insect vectors is an important ingredient in the management of future outbreaks of BT in Europe, and other devastating vector-borne diseases elsewhere.

Statistical models for spatially explicit biological data.

Existing algorithms for predicting species' distributions sit on a continuum between purely statistical and purely biological approaches. Most of the existing algorithms are aspatial because they do not consider the spatial context, the occurrence of the species or conditions conducive to the species' existence, in neighbouring areas. The geostatistical techniques of kriging and cokriging are presented in an attempt to encourage biologists more frequently to consider them. Unlike deterministic spatial techniques they provide estimates of prediction errors. The assumptions and applications of common geostatistical techniques are presented with worked examples drawn from a dataset of the bluetongue outbreak in northwest Europe in 2006. Emphasis is placed on the importance and interpretation of weights in geostatistical calculations. Covarying environmental data may be used to improve predictions of species' distributions, but only if their sampling frequency is greater than that of the species' or disease data. Cokriging techniques are unable to determine the biological significance or importance of such environmental data, because they are not designed to do so.

A taxonomic-based joint species distribution model for presence-only data.

Species distribution models (SDMs) are an important class of model for mapping taxa spatially and are a key tool for tackling biodiversity loss. However, most common SDMs depend on presence-absence data and, despite the accumulation and exponential growth of biological occurrence data across the globe, the available data are predominantly presence-only (i.e. they lack real absences). Although presence-only SDMs do exist, they inevitably require assumptions about absences of the considered taxa and they are specified mostly for single species and, thus, do not exploit fully the information in related taxa. This greatly limits the utility of global biodiversity databases such as GBIF. Here, we present a Bayesian-based SDM for multiple species that operates directly on presence-only data by exploiting the joint distribution between the multiple ecological processes and, crucially, identifies the sampling effort per taxa which allows inference on absences. The model was applied to two case studies. One, focusing on taxonomically diverse taxa over central Mexico and another focusing on the monophyletic family Cactacea over continental Mexico. In both cases, the model was able to identify the ecological and sampling effort processes for each taxon using only the presence observations, environmental and anthropological data.

Comparison of COVID-19 survival in relation to CPAP length of treatment and by comorbidity and transmission setting (community or hospital acquired) in a medium-sized UK hospital in 2020: a retrospective study.

OBJECTIVE: To estimate continuous positive airway pressure (CPAP) length of treatment effect on survival of hospitalised COVID-19 patients in a medium-sized UK Hospital, and how this effect changes according to the patient's comorbidity and COVID-19 route of acquisition (community or nosocomial) during the two waves in 2020. SETTING: The acute inpatient unit in Wrightington, Wigan and Leigh Teaching Hospitals National Health Service (NHS) Foundation Trust (WWL), a medium-sized NHS Trust in north-west of England. DESIGN: Retrospective cohort of all confirmed COVID-19 patients admitted in WWL during 2020. PARTICIPANTS: 1830 patients (568 first wave, 1262 s wave) with antigen confirmed COVID-19 disease and severe acute respiratory syndrome admitted between 17 March 2020 (first confirmed COVID-19 case) and 31 December 2020. OUTCOME MEASURE: COVID-19 survival rate in all patients and survival rate in potentially hospital-acquired COVID-19 (PHA) patients were modelled using a predictor set which include comorbidities (eg, obesity, diabetes, chronic ischaemic heart disease (IHD), chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD)), wave, age, sex and care home residency, and interventions (remdesivir, dexamethasone, CPAP, intensive care unit (ICU), intubation). Secondary outcome measure was CPAP length, which was modelled using the same predictors of the survival rate. RESULTS: Mortality rate in the second wave was significantly lower than in the first wave (43.4% vs 28.1%, p<0.001), although for PHA COVID-19 patients mortality did not reduce, remaining at very high levels independently of wave and CPAP length. For all cohort, statistical modelling identified CPAP length (HR 95% CI 0.86 to 0.96) and women (HR 95% CI 0.71 to 0.81) were associated with improved survival, while being older age (HR 95% CI 1.02 to 1.03) admitted from care homes (HR 95% CI 2.22 to 2.39), IHD (HR 95% CI 1.13 to 1.24), CKD (HR 95% CI 1.14 to 1.25), obesity (HR 95% CI 1.18 to 1.28) and COPD-emphysema (HR 95% CI 1.18 to 1.57) were associated with reduced survival. Despite the detrimental effect of comorbidities, patients with CKD (95% CI 16% to 30% improvement in survival), IHD (95% CI 1% to 10% improvement in survival) and asthma (95% CI 8% to 30% improvement in survival) benefitted most from CPAP length, while no significant survival difference was found for obese and patients with diabetes. CONCLUSIONS: The experience of an Acute Trust during the COVID-19 outbreak of 2020 is documented and indicates the importance of care home and hospitals in disease acquisition. Death rates fell between the first and second wave only for community-acquired COVID-19 patients. The fall was associated to CPAP length, especially for some comorbidities. While uncovering some risk and protective factors of mortality in COVID-19 studies, the study also unravels how little is known about PHA COVID-19 and the interaction between CPAP and some comorbidities.

Review of the ecology and behaviour of Aedes aegypti and Aedes albopictus in Western Africa and implications for vector control.

Western Africa is vulnerable to arboviral disease transmission, having recently experienced major outbreaks of chikungunya, dengue, yellow fever and Zika. However, there have been relatively few studies on the natural history of the two major human arbovirus vectors in this region, Aedes aegypti and Ae. albopictus, potentially limiting the implementation of effective vector control. We systematically searched for and reviewed relevant studies on the behaviour and ecology of Ae. aegypti and Ae. albopictus in Western Africa, published over the last 40 years. We identified 73 relevant studies, over half of which were conducted in Nigeria, Senegal, or Côte d'Ivoire. Most studies investigated the ecology of Ae. aegypti and Ae. albopictus, exploring the impact of seasonality and land cover on mosquito populations and identifying aquatic habitats. This review highlights the adaptation of Ae. albopictus to urban environments and its invasive potential, and the year-round maintenance of Ae. aegypti populations in water storage containers. However, important gaps were identified in the literature on the behaviour of both species, particularly Ae. albopictus. In Western Africa, Ae. aegypti and Ae. albopictus appear to be mainly anthropophilic and to bite predominantly during the day, but further research is needed to confirm this to inform planning of effective vector control strategies. We discuss the public health implications of these findings and comment on the suitability of existing and novel options for control in Western Africa.

Predicting eastern equine encephalitis spread in North America: An ecological study.

Eastern equine encephalitis (EEE) is a rare but lethal mosquito-borne zoonotic disease. Recent years have seen incursion into new areas of the USA, and in 2019 the highest number of human cases in decades. Due to the low detection rate of EEE, previous studies were unable to quantify large-scale and recent EEE ecological dynamics. We used Bayesian spatial generalized-linear mixed model to quantify the spatiotemporal dynamics of human EEE incidence in the northeastern USA. In addition, we assessed whether equine EEE incidence has predictive power for human cases, independently from other environmental variables. The predictors of the model were selected based on variable importance. Human incidence increased with temperature seasonality, but decreased with summer temperature, summer, fall, and winter precipitation. We also found EEE transmission in equines strongly associated with human infection (OR: 1.57; 95% CI: 1.52-1.60) and latitudes above 41.9°N after 2018. The study designed for sparse dataset described new and known relationships between human and animal EEE and environmental factors, including geographical directionality. Future models must include equine cases as a risk factor when predicting human EEE risks. Future work is still necessary to ascertain the establishment of EEE in northern latitudes and the robustness of the available data.

Understanding Mosquito Surveillance Data for Analytic Efforts: A Case Study.

Mosquito surveillance data can be used for predicting mosquito distribution and dynamics as they relate to human disease. Often these data are collected by independent agencies and aggregated to state and national level portals to characterize broad spatial and temporal dynamics. These larger repositories may also share the data for use in mosquito and/or disease prediction and forecasting models. Assumed, but not always confirmed, is consistency of data across agencies. Subtle differences in reporting may be important for development and the eventual interpretation of predictive models. Using mosquito vector surveillance data from Arizona as a case study, we found differences among agencies in how trapping practices were reported. Inconsistencies in reporting may interfere with quantitative comparisons if the user has only cursory familiarity with mosquito surveillance data. Some inconsistencies can be overcome if they are explicit in the metadata while others may yield biased estimates if they are not changed in how data are recorded. Sharing of metadata and collaboration between modelers and vector control agencies is necessary for improving the quality of the estimations. Efforts to improve sharing, displaying, and comparing vector data from multiple agencies are underway, but existing data must be used with caution.

Biospytial: spatial graph-based computing for ecological Big Data.

BACKGROUND: The exponential accumulation of environmental and ecological data together with the adoption of open data initiatives bring opportunities and challenges for integrating and synthesising relevant knowledge that need to be addressed, given the ongoing environmental crises. FINDINGS: Here we present Biospytial, a modular open source knowledge engine designed to import, organise, analyse and visualise big spatial ecological datasets using the power of graph theory. The engine uses a hybrid graph-relational approach to store and access information. A graph data structure uses linkage relationships to build semantic structures represented as complex data structures stored in a graph database, while tabular and geospatial data are stored in an efficient spatial relational database system. We provide an application using information on species occurrences, their taxonomic classification and climatic datasets. We built a knowledge graph of the Tree of Life embedded in an environmental and geographical grid to perform an analysis on threatened species co-occurring with jaguars (Panthera onca). CONCLUSIONS: The Biospytial approach reduces the complexity of joining datasets using multiple tabular relations, while its scalable design eases the problem of merging datasets from different sources. Its modular design makes it possible to distribute several instances simultaneously, allowing fast and efficient handling of big ecological datasets. The provided example demonstrates the engine's capabilities in performing basic graph manipulation, analysis and visualizations of taxonomic groups co-occurring in space. The example shows potential avenues for performing novel ecological analyses, biodiversity syntheses and species distribution models aided by a network of taxonomic and spatial relationships.