Anopheline salivary protein genes and gene families: an evolutionary overview after the whole genome sequence of sixteen Anopheles species

Background: Mosquito saliva is a complex cocktail whose pharmacological properties play an essential role in blood feeding by counteracting host physiological response to tissue injury. Moreover, vector borne pathogens are transmitted to vertebrates and exposed to their immune system in the context of mosquito saliva which, in virtue of its immunomodulatory properties, can modify the local environment at the feeding site and eventually affect pathogen transmission. In addition, the host antibody response to salivary proteins may be used to assess human exposure to mosquito vectors. Even though the role of quite a few mosquito salivary proteins has been clarified in the last decade, we still completely ignore the physiological role of many of them as well as the extent of their involvement in the complex interactions taking place between the mosquito vectors, the pathogens they transmit and the vertebrate host. The recent release of the genomes of 16 Anopheles species offered the opportunity to get insights into function and evolution of salivary protein families in anopheline mosquitoes. Results: Orthologues of fifty three Anopheles gambiae salivary proteins were retrieved and annotated from 18 additional anopheline species belonging to the three subgenera Cellia, Anopheles, and Nyssorhynchus. Our analysis included 824 full-length salivary proteins from 24 different families and allowed the identification of 79 novel salivary genes and re-annotation of 379 wrong predictions. The comparative, structural and phylogenetic analyses yielded an unprecedented view of the anopheline salivary repertoires and of their evolution over 100 million years of anopheline radiation shedding light on mechanisms and evolutionary forces that contributed shaping the anopheline sialomes. Conclusions: We provide here a comprehensive description, classification and evolutionary overview of the main anopheline salivary protein families and identify two novel candidate markers of human exposure to malaria vectors worldwide. This anopheline sialome catalogue, which is easily accessible as hyperlinked spreadsheet, is expected to be useful to the vector biology community and to improve the capacity to gain a deeper understanding of mosquito salivary proteins facilitating their possible exploitation for epidemiological and/or pathogen-vector-host interaction studies

Smart testing and critical care bed sharing for COVID-19 control

During the early months of the current COVID-19 pandemic, social-distancing measures effectively slowed disease transmission in many countries in Europe and Asia, but the same benefits have not been observed in some developing countries such as Brazil. In part, this is due to a failure to organise systematic testing campaigns at nationwide or even regional levels. To gain effective control of the pandemic, decision-makers in developing countries, particularly those with large populations, must overcome difficulties posed by an unequal distribution of wealth combined with low daily testing capacities. The economic infrastructure of the country, often concentrated in a few cities, forces workers to travel from commuter cities and rural areas, which induces strong nonlinear effects on disease transmission. In the present study, we develop a smart testing strategy to identify geographic regions where COVID-19 testing could most effectively be deployed to limit further disease transmission. The strategy uses readily available anonymised mobility and demographic data integrated with intensive care unit (ICU) occupancy data and city-specific social-distancing measures. Taking into account the heterogeneity of ICU bed occupancy in differing regions and the stages of disease evolution, we use a data-driven study of the Brazilian state of Sao Paulo as an example to show that smart testing strategies can rapidly limit transmission while reducing the need for social-distancing measures, thus returning life to a so-called new normal, even when testing capacity is limited

Cost-Effectiveness of Genotype Testing for Primary Resistance in Brazil

Objective: HIV genotype-resistance testing can help identify more effective antiretroviral treatment (ART) regimens for patients, substantially increasing the likelihood of viral suppression and immune recovery. We sought to evaluate the cost-effectiveness of genotype-resistance testing before first-line ART initiation in Brazil. Design: We used a previously published microsimulation model of HIV disease (CEPAC-International) and data from Brazil to compare the clinical impact, costs, and cost-effectiveness of initial genotype testing (Genotype) with no initial genotype testing (No genotype). Methods: Model parameters were derived from the HIV Clinical Cohort at the Evandro Chagas Clinical Research Institute and from published data, using Brazilian sources whenever possible. Baseline patient characteristics included 69% male, mean age of 36 years (SD, 10 years), mean CD4 count of 347 per microliter (SD, 300/µL) at ART initiation, annual ART costs from 2012 US $1400 to US$13,400, genotype test cost of US $230, and primary resistance prevalence of 4.4$12,300. Results: Compared with No genotype, Genotype increased life expectancy from 18.45 to 18.47 years and reduced lifetime cost from US $45,000 to$44,770; thus, in the base case, Genotype was cost saving. Genotype was cost-effective at primary resistance prevalence as low as 1.4% and remained cost-effective when subsequent-line ART costs decreased to 30% of baseline value. Cost-inefficient results were observed only when simultaneously holding multiple parameters to extremes of their plausible ranges. Conclusions: Genotype-resistance testing in ART-naive individuals in Brazil will improve survival and decrease costs and should be incorporated into HIV treatment guidelines in Brazil

Modeling the cost-effectiveness of maternal acellular pertussis immunization (aP) in different socioeconomic settings: A dynamic transmission model of pertussis in three Brazilian states.

OBJECTIVES: Using dynamic transmission models we evaluated the health and cost outcomes of adding acellular pertussis (aP) vaccination of pregnant women to infant vaccination in three Brazilian states that represent different socioeconomic conditions. The primary objective was to determine whether the same model structure could be used to represent pertussis disease dynamics in differing socioeconomic conditions. METHODS: We tested three model structures (SIR, SIRS, SIRSIs) to represent population-level transmission in three socio-demographically distinct Brazilian states: São Paulo, Paraná and Bahia. Two strategies were evaluated: infant wP vaccination alone versus maternal aP immunization plus infant wP vaccination. Model projections for 2014-2029 include outpatient and inpatient pertussis cases, pertussis deaths, years of life lost, disability-adjusted life-years (DALYs) lost, and costs (in 2014 USD) of maternal aP vaccination, infant vaccination, and pertussis medical treatment. Incremental cost per DALY averted is presented from the perspective of the Brazilian National Health System. RESULTS: Based on goodness-of-fit statistics, the SIRSIs model fit best, although it had only a modest improvement in statistical quantitative assessments relative to the SIRS model. For all three Brazilian states, maternal aP immunization led to higher costs but also saved infant lives and averted DALYs. The 2014 USD cost/DALY averted was $3068 in Sao Paulo,$2962 in Parana, and $2022 in Bahia. These results were robust in sensitivity analyses with the incremental cost-effectiveness ratios exceeding per capita gross regional product only when the probability that a pertussis case is reported was assumed higher than base case implying more overt cases and deaths and therefore more medical costs. CONCLUSIONS: The same model structure fit all three states best, supporting the idea that the disease behaves similarly across different socioeconomic conditions. We also found that immunization of pregnant women with aP is cost-effective in diverse Brazilian states

Modeling Transmission Dynamics and Control of Vector-Borne Neglected Tropical Diseases

Neglected tropical diseases affect more than one billion people worldwide. The populations most impacted by such diseases are typically the most resource-limited. Mathematical modeling of disease transmission and cost-effectiveness analyses can play a central role in maximizing the utility of limited resources for neglected tropical diseases. We review the contributions that mathematical modeling has made to optimizing intervention strategies of vector-borne neglected diseases. We propose directions forward in the modeling of these diseases, including integrating new knowledge of vector and pathogen ecology, incorporating evolutionary responses to interventions, and expanding the scope of sensitivity analysis in order to achieve robust results

The cost‐effectiveness of HIV pre‐exposure prophylaxis in men who have sex with men and transgender women at high risk of HIV infection in Brazil

Abstract Introduction: Men who have sex with men (MSM) and transgender women (TGW) in Brazil experience high rates of HIV infection. We examined the clinical and economic outcomes of implementing a pre‐exposure prophylaxis (PrEP) programme in these populations. Methods: We used the Cost‐Effectiveness of Preventing AIDS Complications (CEPAC)‐International model of HIV prevention and treatment to evaluate two strategies: the current standard of care (SOC) in Brazil, including universal ART access (No PrEP strategy); and the current SOC plus daily tenofovir/emtracitabine PrEP (PrEP strategy) until age 50. Mean age (31 years, SD 8.4 years), age‐stratified annual HIV incidence (age ≤ 40 years: 4.3/100 PY; age > 40 years: 1.0/100 PY), PrEP effectiveness (43% HIV incidence reduction) and PrEP drug costs ($23/month) were from Brazil‐based sources. The analysis focused on direct medical costs of HIV care. We measured the comparative value of PrEP in 2015 United States dollars (USD) per year of life saved (YLS). Willingness‐to‐pay threshold was based on Brazil's annual per capita gross domestic product (GDP; 2015:$8540 USD). Results: Lifetime HIV infection risk among high‐risk MSM and TGW was 50.5% with No PrEP and decreased to 40.1% with PrEP. PrEP increased per‐person undiscounted (discounted) life expectancy from 36.8 (20.7) years to 41.0 (22.4) years and lifetime discounted HIV‐related medical costs from $4100 to$8420, which led to an incremental cost‐effectiveness ratio (ICER) of $2530/YLS. PrEP remained cost‐effective (<1x GDP) under plausible variation in key parameters, including PrEP effectiveness and cost, initial cohort age and HIV testing frequency on/off PrEP. Conclusion: Daily tenofovir/emtracitabine PrEP among MSM and TGW at high risk of HIV infection in Brazil would increase life expectancy and be highly cost‐effective

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health