Deployment of attractive targeted sugar baits in western Zambia: installation, monitoring, removal, and disposal procedures during a Phase III cluster randomized controlled trial.

BACKGROUND: Attractive Targeted Sugar Baits (ATSBs) offer a complementary vector control strategy to interventions targeting blood feeding or larval control by attacking the sugar feeding behaviour of adult mosquitoes using an attract-and-kill approach. Western Zambia was the first location to receive and deploy ATSB Sarabi version 1.2 stations in a Phase III cluster randomized controlled trial. This paper describes ATSB station installation, monitoring, removal, and disposal, quantifies ATSB station coverage, and reports major reasons for ATSB station replacement. METHODS: ATSB stations were deployed during two annual transmission seasons, through scheduled installation and removal campaigns. During deployment, monitoring was conducted per protocol to maintain high coverage of the ATSB stations in good condition. Routine monitoring visits during the trial captured details on ATSB station damage necessitating replacement following pre-defined replacement criteria. Annual cross-sectional household surveys measured ATSB station coverage during peak malaria transmission. RESULTS: A total of 67,945 ATSB stations were installed in Year 1 (41,695 initially installed+ 26,250 installed during monitoring) and 69,494 ATSB stations were installed in Year 2 (41,982 initially installed+ 27,512 installed during monitoring) across 35 intervention clusters to maintain high coverage of two ATSB stations in good condition per eligible household structure. The primary reasons for ATSB station replacement due to damage were holes/tears and presence of mold. Cross-sectional household surveys documented high coverage of ATSB stations across Year 1 and Year 2 with 93.1% of eligible structures having ≥ 2 ATSB stations in any condition. DISCUSSION: ATSB station deployment and monitoring efforts were conducted in the context of a controlled cRCT to assess potential product efficacy. Damage to ATSB stations during deployment required replacement of a subset of stations. High coverage of eligible structures was maintained over the two-year study despite replacement requirements. Additional research is needed to better understand the impact of damage on ATSB station effectiveness under programmatic conditions, including thresholds of threats to physical integrity and biological deterioration on product efficacy. CONCLUSIONS: Optimizing ATSB stations to address causes of damage and conducting implementation research to inform optimal delivery and cost-effective deployment will be important to facilitate scale-up of ATSB interventions.

Assessing national vector control micro-planning in Zambia using the 2021 malaria indicator survey.

BACKGROUND: In 2020, the Zambia National Malaria Elimination Centre targeted the distribution of long-lasting insecticidal nets (LLINs) and indoor-residual spraying (IRS) campaigns based on sub-district micro-planning, where specified geographical areas at the health facility catchment level were assigned to receive either LLINs or IRS. Using data from the 2021 Malaria Indicator Survey (MIS), the objectives of this analysis were to (1) assess how well the micro-planning was followed in distributing LLINs and IRS, (2) investigate factors that contributed to whether households received what was planned, and (3) investigate how overall coverage observed in the 2021 MIS compared to the 2018 MIS conducted prior to micro-planning. METHODS: Households' receipt of ≥ 1 LLIN, and/or IRS within the past 12 months in the 2021 MIS, was compared against the micro-planning area under which the households fell. GPS points for 3,550 households were overlayed onto digitized micro-planning maps in order to determine what micro-plan the households fell under, and thus whether they received their planned intervention. Mixed-effects regression models were conducted to investigate what factors affected whether these households: (1) received their planned intervention, and (2) received any intervention. Finally, coverage indicators between the 2021 and 2018 MIS were compared. RESULTS: Overall, 60.0% (95%CI 55.4, 64.4) of households under a micro-plan received their assigned intervention, with significantly higher coverage of the planned intervention in LLIN-assigned areas (75.7% [95%CI 69.5, 80.9]) compared to IRS-assigned areas (49.4% [95%CI: 44.4, 54.4]). Regression analysis indicated that households falling under the IRS micro-plan had significantly reduced odds of receiving their planned intervention (OR: 0.34 [95%CI 0.24, 0.48]), and significantly reduced odds of receiving any intervention (OR: 0.51 [95%CI 0.37, 0.72] ), compared to households under the LLIN micro-plan. Comparison between the 2021 and 2018 MIS indicated a 27% reduction in LLIN coverage nationally in 2021, while IRS coverage was similar. Additionally, between 2018 and 2021, there was a 13% increase in households that received neither intervention. CONCLUSIONS: This analysis shows that although the micro-planning strategy adopted in 2020 worked much better for LLIN-assigned areas compared to IRS-assigned areas, there was reduced overall vector control coverage in 2021 compared to 2018 before micro-planning.

A threshold-free approach with age-dependency for estimating malaria seroprevalence.

BACKGROUND: In malaria serology analysis, the standard approach to obtain seroprevalence, i.e the proportion of seropositive individuals in a population, is based on a threshold which is used to classify individuals as seropositive or seronegative. The choice of this threshold is often arbitrary and is based on methods that ignore the age-dependency of the antibody distribution. METHODS: Using cross-sectional antibody data from the Western Kenyan Highlands, this paper introduces a novel approach that has three main advantages over the current threshold-based approach: it avoids the use of thresholds; it accounts for the age dependency of malaria antibodies; and it allows us to propagate the uncertainty from the classification of individuals into seropositive and seronegative when estimating seroprevalence. The reversible catalytic model is used as an example for illustrating how to propagate this uncertainty into the parameter estimates of the model. RESULTS: This paper finds that accounting for age-dependency leads to a better fit to the data than the standard approach which uses a single threshold across all ages. Additionally, the paper also finds that the proposed threshold-free approach is more robust against the selection of different age-groups when estimating seroprevalence. CONCLUSION: The novel threshold-free approach presented in this paper provides a statistically principled and more objective approach to estimating malaria seroprevalence. The introduced statistical framework also provides a means to compare results across studies which may use different age ranges for the estimation of seroprevalence.

A unified and flexible modelling framework for the analysis of malaria serology data.

Serology data are an increasingly important tool in malaria surveillance, especially in low transmission settings where the estimation of parasite-based indicators is often problematic. Existing methods rely on the use of thresholds to identify seropositive individuals and estimate transmission intensity, while making assumptions about the temporal dynamics of malaria transmission that are rarely questioned. Here, we present a novel threshold-free approach for the analysis of malaria serology data which avoids dichotomization of continuous antibody measurements and allows us to model changes in the antibody distribution across age in a more flexible way. The proposed unified mechanistic model combines the properties of reversible catalytic and antibody acquisition models, and allows for temporally varying boosting and seroconversion rates. Additionally, as an alternative to the unified mechanistic model, we also propose an empirical approach to analysis where modelling of the age-dependency is informed by the data rather than biological assumptions. Using serology data from Western Kenya, we demonstrate both the usefulness and limitations of the novel modelling framework.

The global prevalence of hepatitis D virus infection: Systematic review and meta-analysis.

BACKGROUND AND AIMS: There are uncertainties about the epidemic patterns of HDV infection and its contribution to the burden of liver disease. We estimated the global prevalence of HDV infection and explored its contribution to the development of cirrhosis and hepatocellular carcinoma (HCC) among HBsAg-positive people. METHODS: We searched Pubmed, EMBASE and Scopus for studies reporting on total or IgG anti-HDV among HBsAg-positive people. Anti-HDV prevalence was estimated using a binomial mixed model, weighting for study quality and population size. The population attributable fraction (PAF) of HDV to cirrhosis and HCC among HBsAg-positive people was estimated using random effects models. RESULTS: We included 282 studies, comprising 376 population samples from 95 countries, which together tested 120,293 HBsAg-positive people for anti-HDV. The estimated anti-HDV prevalence was 4.5% (95% CI 3.6-5.7) among all HBsAg-positive people and 16.4% (14.6-18.6) among those attending hepatology clinics. Worldwide, 0.16% (0.11-0.25) of the general population, totalling 12.0 (8.7-18.7) million people, were estimated to be anti-HDV positive. Prevalence among HBsAg-positive people was highest in Mongolia, the Republic of Moldova and countries in Western and Middle Africa, and was higher in injecting drug users, haemodialysis recipients, men who have sex with men, commercial sex workers, and those with HCV or HIV. Among HBsAg-positive people, preliminary PAF estimates of HDV were 18% (10-26) for cirrhosis and 20% (8-33) for HCC. CONCLUSIONS: An estimated 12 million people worldwide have experienced HDV infection, with higher prevalence in certain geographic areas and populations. HDV is a significant contributor to HBV-associated liver disease. More quality data are needed to improve the precision of burden estimates. LAY SUMMARY: We combined all available studies to estimate how many people with hepatitis B also have hepatitis D, a viral infection that only affects people with hepatitis B. About 1 in 22 people with hepatitis B also have hepatitis D, increasing to 1 in 6 when considering people with liver disease. Hepatitis D may cause about 1 in 6 of the cases of cirrhosis and 1 in 5 of the cases of liver cancer that occur in people with hepatitis B. Hepatitis D is an important contributor to the global burden of liver disease.

Correction to: Monitoring changes in malaria epidemiology and effectiveness of interventions in Ethiopia and Uganda: Beyond Garki Project baseline survey.

Please be advised that one of the author names is incorrectly spelled in the published article: 'Irene Kyomuhagi' should be 'Irene Kyomuhangi'.

Insecticide resistance patterns in Uganda and the effect of indoor residual spraying with bendiocarb on kdr L1014S frequencies in Anopheles gambiae s.s.

BACKGROUND: Resistance of malaria vectors to pyrethroid insecticides has been attributed to selection pressure from long-lasting insecticidal nets (LLINs), indoor residual spraying (IRS), and the use of chemicals in agriculture. The use of different classes of insecticides in combination or by rotation has been recommended for resistance management. The aim of this study was to understand the role of IRS with a carbamate insecticide in management of pyrethroid resistance. METHODS: Anopheles mosquitoes were collected from multiple sites in nine districts of Uganda (up to five sites per district). Three districts had been sprayed with bendiocarb. Phenotypic resistance was determined using standard susceptibility tests. Molecular assays were used to determine the frequency of resistance mutations. The kdr L1014S homozygote frequency in Anopheles gambiae s.s. was used as the outcome measure to test the effects of various factors using a logistic regression model. Bendiocarb coverage, annual rainfall, altitude, mosquito collection method, LLIN use, LLINs distributed in the previous 5 years, household use of agricultural pesticides, and malaria prevalence in children 2-9 years old were entered as explanatory variables. RESULTS: Tests with pyrethroid insecticides showed resistance and suspected resistance levels in all districts except Apac (a sprayed district). Bendiocarb resistance was not detected in sprayed sites, but was confirmed in one unsprayed site (Soroti). Anopheles gambiae s.s. collected from areas sprayed with bendiocarb had significantly less kdr homozygosity than those collected from unsprayed areas. Mosquitoes collected indoors as adults had significantly higher frequency of kdr homozygotes than mosquitoes collected as larvae, possibly indicating selective sampling of resistant adults, presumably due to exposure to insecticides inside houses that would disproportionately affect susceptible mosquitoes. The effect of LLIN use on kdr homozygosity was significantly modified by annual rainfall. In areas receiving high rainfall, LLIN use was associated with increased kdr homozygosity and this association weakened as rainfall decreased, indicating more frequency of exposure to pyrethroids in relatively wet areas with high vector density. CONCLUSION: This study suggests that using a carbamate insecticide for IRS in areas with high levels of pyrethroid resistance may reduce kdr frequencies in An. gambiae s.s.

Monitoring changes in malaria epidemiology and effectiveness of interventions in Ethiopia and Uganda: Beyond Garki Project baseline survey.

BACKGROUND: Scale-up of malaria interventions seems to have contributed to a decline in the disease but other factors may also have had some role. Understanding changes in transmission and determinant factors will help to adapt control strategies accordingly. METHODS: Four sites in Ethiopia and Uganda were set up to monitor epidemiological changes and effectiveness of interventions over time. Here, results of a survey during the peak transmission season of 2012 are reported, which will be used as baseline for subsequent surveys and may support adaptation of control strategies. Data on malariometric and entomological variables, socio-economic status (SES) and control coverage were collected. RESULTS: Malaria prevalence varied from 1.4 % in Guba (Ethiopia) to 9.9 % in Butemba (Uganda). The most dominant species was Plasmodium vivax in Ethiopia and Plasmodium falciparum in Uganda. The majority of human-vector contact occurred indoors in Uganda, ranging from 83 % (Anopheles funestus sensu lato) to 93 % (Anopheles gambiae s.l.), which is an important factor for the effectiveness of insecticide-treated nets (ITNs) or indoor residual spraying (IRS). High kdr-L1014S (resistance genotype) frequency was observed in A. gambiae sensu stricto in Uganda. Too few mosquitoes were collected in Ethiopia, so it was not possible to assess vector habits and insecticide resistance levels. ITN ownership did not vary by SES and 56-98 % and 68-78 % of households owned at least one ITN in Ethiopia and Uganda, respectively. In Uganda, 7 % of nets were purchased by households, but the nets were untreated. In three of the four sites, 69-76 % of people with access to ITNs used them. IRS coverage ranged from 84 to 96 % in the three sprayed sites. Half of febrile children in Uganda and three-quarters in Ethiopia for whom treatment was sought received diagnostic tests. High levels of child undernutrition were detected in both countries carrying important implications on child development. In Uganda, 7-8 % of pregnant women took the recommended minimum three doses of intermittent preventive treatment. CONCLUSION: Malaria epidemiology seems to be changing compared to earlier published data, and it is essential to have more data to understand how much of the changes are attributable to interventions and other factors. Regular monitoring will help to better interpret changes, identify determinants, modify strategies and improve targeting to address transmission heterogeneity.