Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study.

BACKGROUND: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. METHODS: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. RESULTS: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95-100) to 100% and specificity from 99% (95% CI 97-100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76-87) to 94% (95% CI 89-98) and specificity ranging from 76% (95% CI 70-82) to 92% (95% CI 88-96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. CONCLUSIONS: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people.Trial Registration NCT04509713 (clinicaltrials.gov).

Risk of Plasmodium falciparum infection in south-west Burkina Faso: potential impact of expanding eligibility for seasonal malaria chemoprevention.

Burkina Faso has one of the highest malaria burdens in sub-Saharan Africa despite the mass deployment of insecticide-treated nets (ITNs) and use of seasonal malaria chemoprevention (SMC) in children aged up to 5 years. Identification of risk factors for Plasmodium falciparum infection in rural Burkina Faso could help to identify and target malaria control measures. A cross-sectional survey of 1,199 children and adults was conducted during the peak malaria transmission season in the Cascades Region of south-west Burkina Faso in 2017. Logistic regression was used to identify risk factors for microscopically confirmed P. falciparum infection. A malaria transmission dynamic model was used to determine the impact on malaria cases averted of administering SMC to children aged 5-15 year old. P. falciparum prevalence was 32.8% in the study population. Children aged 5 to < 10 years old were at 3.74 times the odds (95% CI = 2.68-5.22, P < 0.001) and children aged 10 to 15 years old at 3.14 times the odds (95% CI = 1.20-8.21, P = 0.02) of P. falciparum infection compared to children aged less than 5 years old. Administration of SMC to children aged up to 10 years is predicted to avert an additional 57 malaria cases per 1000 population per year (9.4% reduction) and administration to children aged up to 15 years would avert an additional 89 malaria cases per 1000 population per year (14.6% reduction) in the Cascades Region, assuming current coverage of pyrethroid-piperonyl butoxide ITNs. Malaria infections were high in all age strata, although highest in children aged 5 to 15 years, despite roll out of core malaria control interventions. Given the burden of infection in school-age children, extension of the eligibility criteria for SMC could help reduce the burden of malaria in Burkina Faso and other countries in the region.

Effect of roof colour on indoor temperature and human comfort levels, with implications for malaria control: a pilot study using experimental houses in rural Gambia.

BACKGROUND: In rural sub-Saharan Africa, thatch roofs are being replaced by metal roofs. Metal roofing, however, increases indoor temperatures above human comfort levels, and thus makes it more likely that residents will not use an insecticide-treated bed net (ITN) at night. Whether the colour of a metal roof affects indoor temperature and human comfort was assessed. METHODS: Two identical, experimental houses were constructed with metal roofs in rural Gambia. Roof types were: (1) original bare-metal, (2) painted with red oxide primer or (3) white gloss, to reflect solar radiation. Pairwise comparisons were run in six, five-night blocks during the malaria season 2018. Indoor climate was measured in each house and multivariate analysis used to compare indoor temperatures during the day and night. RESULTS: From 21.00 to 23.59 h, when most residents decide whether to use an ITN or not, the indoor temperature of a house with a bare metal roof was 31.5 °C (95% CI 31.2-31.8 °C), a red roof, 30.3 °C (95% CI 30.0-30.6) and a white roof, 29.8 °C (95% CI 29.4-30.1). During the same period, red-roofed houses were 1.23 °C cooler (95% CI 1.22-1.23) and white roofs 1.74 °C cooler (95% CI 1.70-1.79) than bare-metal roofed houses (p < 0.001). Similar results were found from 00.00 to 06.00 h. Maximum daily temperatures were 0.93 °C lower in a white-roofed house (95% CI 0.10-0.30, p < 0.001), but not a red roof (mean maximum temperature difference = 0.44 °C warmer, 95% CI 0.43-0.45, p = 0.081), compared with the bare-metal roofed houses. Human comfort analysis showed that from 21.00 to 23.59 h houses with white roofs (comfortable for 87% time) were more comfortable than bare-metal roofed houses (comfortable for 13% time; odds ratio = 43.7, 95% CI 27.5-69.5, p < 0.001). The cost of painting a metal roof white is approximately 31-68 USD. CONCLUSIONS: Houses with a white roof were consistently cooler and more comfortable than those with a bare metal roof. Painting the roofs of houses white is a cheap way of making a dwelling more comfortable for the occupants and could potentially increase bed net use in hot humid countries.

Improved housing versus usual practice for additional protection against clinical malaria in The Gambia (RooPfs): a household-randomised controlled trial.

BACKGROUND: In malaria-endemic areas, residents of modern houses have less malaria than those living in traditional houses. We aimed to assess whether children in The Gambia received an incremental benefit from improved housing, where current best practice of insecticide-treated nets, indoor residual spraying, seasonal malaria chemoprevention in children younger than 5 years, and prompt treatment against clinical malaria was in place. METHODS: In this randomised controlled study, 800 households with traditional thatched-roofed houses were randomly selected from 91 villages in the Upper River Region of The Gambia. Within each village, equal numbers of houses were randomly allocated to the control and intervention groups using a sampling frame. Houses in the intervention group were modified with metal roofs and screened doors and windows, whereas houses in the control group received no modifications. In each group, clinical malaria in children aged 6 months to 13 years was monitored by active case detection over 2 years (2016-17). We did monthly collections from indoor light traps to estimate vector densities. Primary endpoints were the incidence of clinical malaria in study children with more than 50% of observations each year and household vector density. The trial is registered at ISRCTN02622179. FINDINGS: In June, 2016, 785 houses had one child each recruited into the study (398 in unmodified houses and 402 in modified houses). 26 children in unmodified houses and 28 children in modified houses did not have at least 50% of visits in a year and so were excluded from analysis. 38 children in unmodified houses were recruited after study commencement, as were 21 children in modified houses, meaning 410 children in unmodified houses and 395 in modified houses were included in the parasitological analyses. At the end of the study, 659 (94%) of 702 children were reported to have slept under an insecticide-treated net; 662 (88%) of 755 children lived in houses that received indoor residual spraying; and 151 (90%) of 168 children younger than 5 years had seasonal malaria chemoprevention. Incidence of clinical malaria was 0·12 episodes per child-year in children in the unmodified houses and 0·20 episodes per child-year in the modified houses (unadjusted incidence rate ratio [RR] 1·68 [95% CI 1·11-2·55], p=0·014). Household vector density was 3·30 Anopheles gambiae per house per night in the unmodified houses compared with 3·60 in modified houses (unadjusted RR 1·28 [0·87-1·89], p=0·21). INTERPRETATION: Improved housing did not provide protection against clinical malaria in this area of low seasonal transmission with high coverage of insecticide-treated nets, indoor residual spraying, and seasonal malaria chemoprevention. FUNDING: Global Health Trials funded by Medical Research Council, UK Department for International Development, and Wellcome Trust.

Can the buck always be passed to the highest level of clustering?

BACKGROUND: Clustering commonly affects the uncertainty of parameter estimates in epidemiological studies. Cluster-robust variance estimates (CRVE) are used to construct confidence intervals that account for single-level clustering, and are easily implemented in standard software. When data are clustered at more than one level (e.g. village and household) the level for the CRVE must be chosen. CRVE are consistent when used at the higher level of clustering (village), but since there are fewer clusters at the higher level, and consistency is an asymptotic property, there may be circumstances under which coverage is better from lower- rather than higher-level CRVE. Here we assess the relative importance of adjusting for clustering at the higher and lower level in a logistic regression model. METHODS: We performed a simulation study in which the coverage of 95 % confidence intervals was compared between adjustments at the higher and lower levels. RESULTS: Confidence intervals adjusted for the higher level of clustering had coverage close to 95 %, even when there were few clusters, provided that the intra-cluster correlation of the predictor was less than 0.5 for models with a single predictor and less than 0.2 for models with multiple predictors. CONCLUSIONS: When there are multiple levels of clustering it is generally preferable to use confidence intervals that account for the highest level of clustering. This only fails if there are few clusters at this level and the intra-cluster correlation of the predictor is high.