Semi-field evaluation of freestanding transfluthrin passive emanators and the BG sentinel trap as a "push-pull control strategy" against Aedes aegypti mosquitoes

Spatial repellents that drive mosquitoes away from treated areas, and odour-baited traps, that attract and kill mosquitoes, can be combined and work synergistically in a push-pull system. Push-pull systems have been shown to reduce house entry and outdoor biting rates of malaria vectors and so have the potential to control other outdoor biting mosquitoes such as Aedes aegypti that transmit arboviral diseases. In this study, semi-field experiments were conducted to evaluate whether a push-pull system could be used to reduce bites from Aedes mosquitoes.; The push and pull under investigation consisted of two freestanding transfluthrin passive emanators (FTPE) and a BG sentinel trap (BGS) respectively. The FTPE contained hessian strips treated with 5.25 g of transfluthrin active ingredient. The efficacies of FTPE and BGS alone and in combination were evaluated by human landing catch in a large semi-field system in Tanzania. We also investigated the protection of FTPE over six months. The data were analyzed using generalized linear mixed models with binomial distribution.; Two FTPE had a protective efficacy (PE) of 61.2% (95% confidence interval (CI): 52.2-69.9%) against the human landing of Ae. aegypti. The BGS did not significantly reduce mosquito landings; the PE was 2.1% (95% CI: -2.9-7.2%). The push-pull provided a PE of 64.5% (95% CI: 59.1-69.9%). However, there was no significant difference in the PE between the push-pull and the two FTPE against Ae. aegypti (P = 0.30). The FTPE offered significant protection against Ae. aegypti at month three, with a PE of 46.4% (95% CI: 41.1-51.8%), but not at six months with a PE of 2.2% (95% CI: -9.0-14.0%).; The PE of the FTPE and the full push-pull are similar, indicative that bite prevention is primarily due to the activity of the FTPE. While these results are encouraging for the FTPE, further work is needed for a push-pull system to be recommended for Ae. aegypti control. The three-month protection against Ae. aegypti bites suggests that FTPE would be a useful additional control tool during dengue outbreaks, that does not require regular user compliance

Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis

Background: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria screening, directly from dried human blood spots. Methods: Filter papers containing dried blood spots (DBS) were obtained from a cross-sectional malaria survey in 12 wards in southeastern Tanzania in 2018/19. The DBS were scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra in the range 4000 cm−1 to 500 cm−1. The spectra were cleaned to compensate for atmospheric water vapour and CO2 interference bands and used to train different classification algorithms to distinguish between malaria-positive and malaria-negative DBS papers based on PCR test results as reference. The analysis considered 296 individuals, including 123 PCR-confirmed malaria positives and 173 negatives. Model training was done using 80% of the dataset, after which the best-fitting model was optimized by bootstrapping of 80/20 train/test-stratified splits. The trained models were evaluated by predicting Plasmodium falciparum positivity in the 20% validation set of DBS. Results: Logistic regression was the best-performing model. Considering PCR as reference, the models attained overall accuracies of 92% for predicting P. falciparum infections (specificity = 91.7%; sensitivity = 92.8%) and 85% for predicting mixed infections of P. falciparum and Plasmodium ovale (specificity = 85%, sensitivity = 85%) in the field-collected specimen. Conclusion: These results demonstrate that mid-infrared spectroscopy coupled with supervised machine learning (MIR-ML) could be used to screen for malaria parasites in human DBS. The approach could have potential for rapid and high-throughput screening of Plasmodium in both non-clinical settings (e.g., field surveys) and clinical settings (diagnosis to aid case management). However, before the approach can be used, we need additional field validation in other study sites with different parasite populations, and in-depth evaluation of the biological basis of the MIR signals. Improving the classification algorithms, and model training on larger datasets could also improve specificity and sensitivity. The MIR-ML spectroscopy system is physically robust, low-cost, and requires minimum maintenance

Combining Geoprocessing and Interregional Input-Output Systems: An Application to the State of São Paulo in Brazil

This work develops a method for the construction of input-output systems capable of estimating the flows of goods and services among cities, having in view that the creation of accurate strategies depends on the regional peculiarities incorporated in the scope of the economic planning researches. The study innovates by combining geoprocessing with inputoutput theory elements, facilitating the interpretation of the information available on the extensive data set of interregional input-output systems. The analytical potential is showed through a panoramic evaluation of the São Paulo State supply and demand relations, and by the application of the estimated input-output system to a study of the regional impacts of the “Bolsa Familia” Program, an income transfer program from the Federal government. The results show that this program must be understood not only as a form of income transference, but also as a catalytic agent for decreasing the regional inequality inside the state