Explore the vast range of titles available.

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40, 000 ecologically and genetically diverse An. gambiae , An. arabiensis , and An. coluzzii females, we develop a deep transfer learning model that learns and predicts the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model is able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases. Knowing the age of malaria-transmitting mosquitoes is important to understand transmission risk as only old mosquitoes can transmit the disease. Here, the authors develop a method based on mid-infrared spectra of mosquito cuticle that can rapidly identify the species and age class of main malaria vectors.

In the past decades, dengue incidence has dramatically increased all over the world. An emerging dengue control strategy utilizes Aedes aegypti mosquitoes artificially transinfected with the bacterial symbiont Wolbachia , with the ultimate aim of replacing wild mosquito populations. Environmental factors play a crucial role in the population dynamics of arthropod endosymbionts, and therefore in the deployment of Wolbachia symbionts for the control of dengue arboviruses. The potential of Wolbachia to invade, persist, and block virus transmission depends in part on its intracellular density. Several recent studies have highlighted the importance of larval rearing temperature in modulating Wolbachia densities in adults, suggesting that elevated temperatures can severely impact some strains, while having little effect on others. The effect of a replicated tropical heat cycle on Wolbachia density and levels of virus blocking was assessed using Aedes aegypti lines carrying strains w Mel and w AlbB, two Wolbachia strains currently used for dengue control. Impacts on intracellular density, maternal transmission fidelity, and dengue inhibition capacity were observed for w Mel. In contrast, w AlbB-carrying Ae. aegypti maintained a relatively constant intracellular density at high temperatures and conserved its capacity to inhibit dengue. Following larval heat treatment, w Mel showed a degree of density recovery in aging adults, although this was compromised by elevated air temperatures. IMPORTANCE In the past decades, dengue incidence has dramatically increased all over the world. An emerging dengue control strategy utilizes Aedes aegypti mosquitoes artificially transinfected with the bacterial symbiont Wolbachia , with the ultimate aim of replacing wild mosquito populations. However, the rearing temperature of mosquito larvae is known to impact on some Wolbachia strains. In this study, we compared the effects of a temperature cycle mimicking natural breeding sites in tropical climates on two Wolbachia strains, currently used for open field trials. When choosing the Wolbachia strain to be used in a dengue control program it is important to consider the effects of environmental temperatures on invasiveness and virus inhibition. These results underline the significance of understanding the impact of environmental factors on released mosquitoes, in order to ensure the most efficient strategy for dengue control.

Occasional risk of serious liver dysfunction and autoimmune hepatitis during atorvastatin therapy has been reported. We compared the risk of hepatotoxicity in atorvastatin relative to simvastatin treatment. The UK GPRD identified patients with a first prescription for simvastatin [164,407] or atorvastatin [76,411] between 1997 and 2006, but with no prior record of liver disease, alcohol-related diagnosis, or liver dysfunction. Incident liver dysfunction in the following six months was identified by biochemical value and compared between statin groups by Cox regression model adjusting for age, sex, year treatment started, dose, alcohol consumption, smoking, body mass index and comorbid conditions. Moderate to severe hepatotoxicity [bilirubin >60μmol/L, AST or ALT >200U/L or alkaline phosphatase >1200U/L] developed in 71 patients on atorvastatin versus 101 on simvastatin. Adjusted hazard ratio [AHR] for all atorvastatin relative to simvastatin was 1.9 [95% confidence interval 1.4-2.6]. High dose was classified as 40-80mg daily and low dose 10-20mg daily. Hepatotoxicity occurred in 0.44% of 4075 patients on high dose atorvastatin [HDA], 0.07% of 72,336 on low dose atorvastatin [LDA], 0.09% of 44,675 on high dose simvastatin [HDS] and 0.05% of 119,732 on low dose simvastatin [LDS]. AHRs compared to LDS were 7.3 [4.2-12.7] for HDA, 1.4 [0.9-2.0] for LDA and 1.5 [1.0-2.2] for HDS. The risk of hepatotoxicity was increased in the first six months of atorvastatin compared to simvastatin treatment, with the greatest difference between high dose atorvastatin and low dose simvastatin. The numbers of events in the analyses were small.

Background The use of insecticide-treated nets for malaria control has been associated with shifts in mosquito vector feeding behaviour including earlier and outdoor biting on humans. The relative contribution of phenotypic plasticity and heritability to these behavioural shifts is unknown. Elucidation of the mechanisms behind these shifts is crucial for anticipating impacts on vector control. Methods A novel portable semi-field system (PSFS) was used to experimentally measure heritability of biting time in the malaria vector Anopheles arabiensis in Tanzania. Wild An. arabiensis from hourly collections using the human landing catch (HLC) method were grouped into one of 3 categories based on their time of capture: early (18:00–21:00), mid (22:00–04:00), and late (05:00–07:00) biting, and placed in separate holding cages. Mosquitoes were then provided with a blood meal for egg production and formation of first filial generation (F1). The F1 generation of each biting time phenotype category was reared separately, and blood fed at the same time as their mothers were captured host-seeking. The resultant eggs were used to generate the F2 generation for use in heritability assays. Heritability was assessed by releasing F2 An. arabiensis into the PSFS, recording their biting time during a human landing catch and comparing it to that of their F0 grandmothers. Results In PSFS assays, the biting time of F2 offspring (early: 18:00–21:00, mid: 22:00–04:00 or late: 05:00–07:00) was significantly positively associated with that of their wild-caught F0 grandmothers, corresponding to an estimated heritability of 0.110 (95% CI 0.003, 0.208). F2 from early-biting F0 were more likely to bite early than F2 from mid or late-biting F0. Similarly, the probability of biting late was higher in F2 derived from mid and late-biting F0 than from early-biting F0. Conclusions Despite modest heritability, our results suggest that some of the variation in biting time is attributable to additive genetic variation. Selection can, therefore, act efficiently on mosquito biting times, highlighting the need for control methods that target early and outdoor biting mosquitoes.

Background Semi-field experiments are an efficient way of assessing the impacts of potential new vector control tools (VCTs) before field trials. However, their design is critically important to ensure their results are unbiased and informative. An essential element of the design of semi-field experiments is power analysis, which empowers researchers to ensure that only designs with adequate statistical power are adopted. In this study, a methodology was developed, and its use was demonstrated in a tutorial, to determine the required number of semi-field chambers, sampling frequency and the number of mosquitoes required to achieve sufficient power for evaluating the impact of a single VCT or two in combination. Methods By analysing data simulated from a generalized linear mixed-effects model, power was estimated for various experimental designs, including short- (24 h) vs. long-term (3 months) experiments and single vs. combined application of interventions (e.g., insecticide-treated nets combined with pyriproxyfen autodissemination). Results Although power increased with increasing number of chambers, sampling frequency and the number of mosquitoes, the number of chambers and variance between chambers were the dominant factors determining power relative to all other design choices. High variance between chambers decreased power, highlighting the importance of making conditions similar among chambers, by reducing variation if possible and by rotating variables if not . As compared to a single intervention, an additional intervention required an increase in the number of chambers, while short and long experiments were similar in terms of key aspects such as the number of chambers per treatment. Conclusion Determining the most efficient experimental design for a semi-field experiment will depend on a balance of design choices and resource constraints. The power analysis framework and tutorial provided here can aid in the robust design of these widely used experiments and ultimately facilitate the development of new vector control tools (VCTs).

The human respiratory tract hosts a diverse community of cocirculating viruses that are responsible for acute respiratory infections. This shared niche provides the opportunity for virus–virus interactions which have the potential to affect individual infection risks and in turn influence dynamics of infection at population scales. However, quantitative evidence for interactions has lacked suitable data and appropriate analytical tools. Here, we expose and quantify interactions among respiratory viruses using bespoke analyses of infection time series at the population scale and coinfections at the individual host scale. We analyzed diagnostic data from 44,230 cases of respiratory illness that were tested for 11 taxonomically broad groups of respiratory viruses over 9 y. Key to our analyses was accounting for alternative drivers of correlated infection frequency, such as age and seasonal dependencies in infection risk, allowing us to obtain strong support for the existence of negative interactions between influenza and noninfluenza viruses and positive interactions among noninfluenza viruses. In mathematical simulations that mimic 2-pathogen dynamics, we show that transient immune-mediated interference can cause a relatively ubiquitous common cold-like virus to diminish during peak activity of a seasonal virus, supporting the potential role of innate immunity in driving the asynchronous circulation of influenza A and rhinovirus. These findings have important implications for understanding the linked epidemiological dynamics of viral respiratory infections, an important step towards improved accuracy of disease forecasting models and evaluation of disease control interventions.

Antiviral defenses can sense viral RNAs and mediate their destruction. This presents a challenge for host cells since they must destroy viral RNAs while sparing the host mRNAs that encode antiviral effectors. Here, we show that highly upregulated interferon-stimulated genes (ISGs), which encode antiviral proteins, have distinctive nucleotide compositions. We propose that self-targeting by antiviral effectors has selected for ISG transcripts that occupy a less self-targeted sequence space. Following interferon (IFN) stimulation, the CpG-targeting antiviral effector zinc-finger antiviral protein (ZAP) reduces the mRNA abundance of multiple host transcripts, providing a mechanistic explanation for the repression of many (but not all) interferon-repressed genes (IRGs). Notably, IRGs tend to be relatively CpG rich. In contrast, highly upregulated ISGs tend to be strongly CpG suppressed. Thus, ZAP is an example of an effector that has not only selected compositional biases in viral genomes but also appears to have notably shaped the composition of host transcripts in the vertebrate interferome.

This manuscript is a master statistical analysis plan for each of three-cluster randomized controlled trials to evaluate the efficacy of attractive targeted sugar baits (ATSB) described in an already published protocol. The master SAP contains an overarching plan for all three trials, which can be adapted to trial-specific circumstances. The primary objective of the trials is to evaluate the efficacy of ATSB in the presence of universal vector control coverage with insecticide-treated nets (ITN) or indoor residual spraying (IRS) after two transmission seasons on clinical malaria incidence as compared with universal vector control coverage with ITN or IRS alone. The primary outcome measure is the incidence rate of clinical malaria, assessed in cohorts aged 12 months to less than 15 years (≥ 5 years to 15 years in Mali) during monthly follow-up visits. The primary unadjusted analysis will be conducted on the intention-to-treat analysis population without adjustment for any anticipated confounding variables. The primary outcome will be analyzed using a multi-level model constructed on a generalized linear model framework with a Poisson likelihood and a log link function. Random intercepts will be included for each study cluster and a fixed effect for study-arm. The analyst will be blinded to study arm assignment. Several secondary outcomes will be analyzed, as well as a pooled analysis (individual patient data meta-analysis) across the three trial sites. Additionally, a standard meta-analysis is expected to be conducted using combined data from all sites.

It has previously been hypothesized that lower socio-economic status can accelerate biological ageing, and predispose to early onset of disease. This study investigated the association of socio-economic and lifestyle factors, as well as traditional and novel risk factors, with biological-ageing, as measured by telomere length, in a Glasgow based cohort that included individuals with extreme socio-economic differences. A total of 382 blood samples from the pSoBid study were available for telomere analysis. For each participant, data was available for socio-economic status factors, biochemical parameters and dietary intake. Statistical analyses were undertaken to investigate the association between telomere lengths and these aforementioned parameters. The rate of age-related telomere attrition was significantly associated with low relative income, housing tenure and poor diet. Notably, telomere length was positively associated with LDL and total cholesterol levels, but inversely correlated to circulating IL-6. These data suggest lower socio-economic status and poor diet are relevant to accelerated biological ageing. They also suggest potential associations between elevated circulating IL-6, a measure known to predict cardiovascular disease and diabetes with biological ageing. These observations require further study to tease out potential mechanistic links.

Livestock brucellosis is an endemic disease in many low-resource settings. Despite its widespread distribution, little is known about the scale of economic impacts caused by the disease. This study aimed to develop an integrated epidemiological-economic modelling framework to estimate production losses attributable to livestock brucellosis, using Tanzania as a case study. Data on livestock production and prevalence of exposure to Brucella spp. were obtained from surveys conducted in northern and central Tanzania between 2013 and 2019. A clustering algorithm was applied to classify households into pastoral and non-pastoral production systems. A Bayesian latent-class analysis model was applied to derive livestock brucellosis prevalence estimates. A herd-growth model was used to estimate production losses attributable to brucellosis. A total of 1,541 households (384 classified as pastoral and 1,157 as non-pastoral) contributed data on livestock production or prevalence of exposure to Brucella spp. The median (95% uncertainty interval, UI) individual-level brucellosis prevalence in cattle, sheep, and goats was 5.1% (3.4–6.9), 1.3% (0.1–3.0), and 2.5% (0.3–4.8) in the pastoral system, and 0.7% (0.1–1.6), 1.6% (0.2–3.8), and 2.5% (0.3–4.9) in the non-pastoral system, respectively. The median (95% UI) annual losses attributable to brucellosis in cattle, sheep, and goats, per infected animal, were 74.4 (26.2–211.7), 9.7 (3.4–23.1) and 10.6 (3.7–25.0) international dollars (int.$) in the pastoral system, and 62.3 (16.8–228.6), 6.3 (1.8–17.1) and 7.0 (2.2–17.9) int. $in the non-pastoral system, respectively. Household-level losses were equivalent to 4.4% (2.1–8.8) and 0.6% (0.2–1.6) of the median (95% UI) livestock-derived income in the pastoral and non-pastoral systems, respectively. This study did not capture the system-wide impacts of brucellosis, including on human health. The estimated losses are only a part of the full societal economic impact of the disease. These results can be used to inform cost-benefit analyses of potential interventions and guide policy development for brucellosis control.