House modifications for preventing malaria

Abstract

Background: Despite being preventable, malaria remains an important public health problem. The World Health Organization (WHO) reports that overall progress in malaria control has plateaued for the first time since the turn of the century. Researchers and policymakers are therefore exploring alternative and supplementary malaria vector control tools. Research in 1900 indicated that modification of houses may be effective in reducing malaria: this is now being revisited, with new research now examining blocking house mosquito entry points or modifying house construction materials to reduce exposure of inhabitants to infectious bites.

Objectives: To assess the effects of house modifications on malaria disease and transmission.

Search methods: We searched the Cochrane Infectious Diseases Group Specialized Register; Central Register of Controlled Trials (CENTRAL), published in the Cochrane Library; MEDLINE (PubMed); Embase (OVID); Centre for Agriculture and Bioscience International (CAB) Abstracts (Web of Science); and the Latin American and Caribbean Health Science Information database (LILACS), up to 1 November 2019. We also searched the WHO International Clinical Trials Registry Platform (www.who.int/ictrp/search/en/), ClinicalTrials.gov (www.clinicaltrials.gov), and the ISRCTN registry (www.isrctn.com/) to identify ongoing trials up to the same date.

Selection criteria: Randomized controlled trials, including cluster-randomized controlled trials (cRCTs), cross-over studies, and stepped-wedge designs were eligible, as were quasi-experimental trials, including controlled before-and-after studies, controlled interrupted time series, and non-randomized cross-over studies. We only considered studies reporting epidemiological outcomes (malaria case incidence, malaria infection incidence or parasite prevalence). We also summarised qualitative studies conducted alongside included studies.

Data collection and analysis: Two review authors selected eligible studies, extracted data, and assessed the risk of bias. We used risk ratios (RR) to compare the effect of the intervention with the control for dichotomous data. For continuous data, we presented the mean difference; and for count and rate data, we used rate ratios. We presented all results with 95% confidence intervals (CIs). We assessed the certainty of evidence using the GRADE approach.

Main results: Six cRCTs met our inclusion criteria, all conducted in sub-Saharan Africa; three randomized by household, two by village, and one at the community level. All trials assessed screening of windows, doors, eaves, ceilings or any combination of these; this was either alone, or in combination with eave closure, roof modification or eave tube installation (a "lure and kill" device that reduces mosquito entry whilst maintaining some airflow). In two trials, the interventions were insecticide-based. In five trials, the researchers implemented the interventions. The community implemented the interventions in the sixth trial. At the time of writing the review, two of the six trials had published results, both of which compared screened houses (without insecticide) to unscreened houses. One trial in Ethiopia assessed screening of windows and doors. Another trial in the Gambia assessed full screening (screening of eaves, doors and windows), as well as screening of ceilings only. Screening may reduce clinical malaria incidence caused by Plasmodium falciparum (rate ratio 0.38, 95% CI 0.18 to 0.82; 1 trial, 184 participants, 219.3 person-years; low-certainty evidence; Ethiopian study). For malaria parasite prevalence, the point estimate, derived from The Gambia study, was smaller (RR 0.84, 95% CI 0.60 to 1.17; 713 participants, 1 trial; low-certainty evidence), and showed an effect on anaemia (RR 0.61, 95% CI 0.42, 0.89; 705 participants; 1 trial, moderate-certainty evidence). Screening may reduce the entomological inoculation rate (EIR): both trials showed lower estimates in the intervention arm. In the Gambian trial, there was a mean difference in EIR between the control houses and treatment houses ranging from 0.45 to 1.50 (CIs ranged from -0.46 to 2.41; low-certainty evidence), depending on the study year and treatment arm. The Ethiopian trial reported a mean difference in EIR of 4.57, favouring screening (95% CI 3.81 to 5.33; low-certainty evidence). Pooled analysis of the trials showed that individuals living in fully screened houses were slightly less likely to sleep under a bed net (RR 0.84, 95% CI 0.65 to 1.09; 2 trials, 203 participants). In one trial, bed net usage was also lower in individuals living in houses with screened ceilings (RR 0.69, 95% CI 0.50 to 0.95; 1 trial, 135 participants).

Authors' conclusions: Based on the two trials published to date, there is some evidence that screening may reduce malaria transmission and malaria infection in people living in the house. The four trials awaiting publication are likely to enrich the current evidence base, and we will add these to this review when they become available.

1

Logic model showing the sectors involved, and potential long and short‐term outcomes associated with house modifications.

2

PRISMA diagram
^aOne study examining user acceptability was identified through searching for any studies conducted alongside those identified through database searching. This study was included in both qualitative and quantitative synthesis.

3

Risk of bias summary: review authors' judgements about each risk of bias item for each included study.

1.1. Analysis

Comparison 1: Screening versus no screening, Outcome 1: Clinical P falciparum malaria incidence

1.2. Analysis

Comparison 1: Screening versus no screening, Outcome 2: Malaria parasite prevalence

1.3. Analysis

Comparison 1: Screening versus no screening, Outcome 3: Anaemia (haemoglobin conc <80g/L) prevalence

1.4. Analysis

Comparison 1: Screening versus no screening, Outcome 4: Bed net use (primary analysis, assuming ICC of 0.375)

1.5. Analysis

Comparison 1: Screening versus no screening, Outcome 5: Bed net use (sensitivity analysis, ICC=0.3)

1.6. Analysis

Comparison 1: Screening versus no screening, Outcome 6: Bed net use (sensitivity analysis, ICC=0.45)