Threshold-free statistical methods for the analysis of continuous health outcomes, with applications to malaria serology

Continuous measurements of health outcome data are often dichotomized into binary ( i.e. positive/negative) data for diagnosis and subsequent statistical analysis. The disadvantages of dichotomizing continuous data for statistical inference are well established in the literature, yet this practice is commonplace in health research. In this thesis, we investigate the impact of dichotomization of data when the aim of analysis is to determine disease prevalence and risk, and propose solutions to some of the main challenges introduced by dichotomization in the context of global heath research. First, using model-based geostatistics, we show how dichotomization reduces the predictive performance of geostatistical models through loss of information and by reducing the reliability of parameter estimates. We demonstrate this using a simulation study, as well as mapping prevalence and risk of anaemia in Ethiopia, and stunting in Ghana. We then explore the limitations dichotomization introduces to estimation of malaria transmission in serology models, and propose a novel flexible and unified modelling framework which uses continuous antibody measurements instead of dichotomized data to estimate transmission intensity. Using Western Kenya, we demonstrate the properties of this new approach. Finally, we address the use of thresholds for dichotomization of continuous antibody measurements when the goal is to estimate malaria seroprevalence. We utilize the principles of the unified modelling framework to develop a threshold-free approach to estimating seroprevalence. Using the same Western Kenyan data-set, we show how this new approach improves model fit and provides more consistent estimates than traditional methods. Together, these investigations demonstrate the significant impact dichotomization of continuous data has on statistical inference across different areas of health research, and that this practice should be avoided where possible

Understanding the effects of dichotomization of continuous outcomes on geostatistical inference

Diagnosis is often based on the exceedance or not of continuous health indicators of a predefined cut-off value, so as to classify patients into positives and negatives for the disease under investigation. In this paper, we investigate the effects of dichotomization of spatially-referenced continuous outcome variables on geostatistical inference. Although this issue has been extensively studied in other fields, dichotomization is still a common practice in epidemiological studies. Furthermore, the effects of this practice in the context of prevalence mapping have not been fully understood. Here, we demonstrate how spatial correlation affects the loss of information due to dichotomization, how linear geostatistical models can be used to map disease prevalence and thus avoid dichotomization, and finally, how dichotomization affects our predictive inference on prevalence. To pursue these objectives, we develop a metric, based on the composite likelihood, which can be used to quantify the potential loss of information after dichotomization without requiring the fitting of Binomial geostatistical models. Through a simulation study and two applications on disease mapping in Africa, we show that, as thresholds used for dichotomization move further away from the mean of the underlying process, the performance of binomial geostatistical models deteriorates substantially. We also find that dichotomization can lead to the loss of fine scale features of disease prevalence and increased uncertainty in the parameter estimates, especially in the presence of a large noise to signal ratio. These findings strongly support the conclusions from previous studies that dichotomization should be always avoided whenever feasible

The global prevalence of hepatitis D virus infection : systematic review and metaanalysis

Background and Aims There are uncertainties about the epidemic patterns of hepatitis delta virus (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 hepatitis B surface antigen (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 hepatitis C virus 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 precisions of burden estimates

Why does malaria transmission continue at high levels despite universal vector control? Quantifying persistent malaria transmission by Anopheles funestus in Western Province, Zambia.

BACKGROUND: Some settings continue to experience a high malaria burden despite scale-up of malaria vector control to high levels of coverage. Characterisation of persistent malaria transmission in the presence of standard control measures, also termed residual malaria transmission, to understand where and when individuals are exposed to vector biting is critical to inform refinement of prevention and control strategies. METHODS: Secondary analysis was performed using data collected during a phase III cluster randomized trial of attractive targeted sugar bait stations in Western Province, Zambia. Two seasonal cohorts of children aged 1-14 years were recruited and monitored monthly during the malaria transmission season, concurrent with entomological surveillance using a combination of human landing catch (HLC) and Centres for Disease Control (CDC) light traps at randomly selected households in study clusters. Behavioural data from cohort participants were combined with measured Anopheles funestus landing rates and sporozoite positivity to estimate the human behaviour-adjusted entomological inoculation rate (EIR). RESULTS: Behavioural data from 1237 children over 5456 child-visits in 20 entomology surveillance clusters were linked with hourly landing rates from 8131 female An. funestus trapped by HLC. Among all An. funestus tested by enzyme-linked immunosorbent assay (ELISA), 3.3% were sporozoite-positive. Mean EIR directly measured from HLC was 0.07 infectious bites per person per night (ib/p/n). When accounting for child locations over the evening and night, the mean behaviour-adjusted EIR was 0.02 ib/p/n. Children not sleeping under insecticide-treated nets (ITNs) experienced 13.6 infectious bites per person per 6 month season, 8% of which occurred outdoors, while ITN users received 1.3 infectious bites per person per 6 month season, 86% of which were received outdoors. Sleeping under an ITN can prevent approximately 90% of potential An. funestus bites among children. CONCLUSIONS: In this setting ITNs have a high personal protective efficacy owing to peak An. funestus biting occurring indoors while most individuals are asleep. However, despite high household possession of ITNs (>90%) and high individual use (>70%), children in this setting experience more than one infectious bite per person per 6 month transmission season, sufficient to maintain high malaria transmission and burden. New tools and strategies are required to reduce the malaria burden in such settings

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

Hepatitis D prevalence: problems with extrapolation to global population estimates.

We read the meta-analysis of global hepatitis D prevalence by Chen et al and have some serious concerns relating to the proposed epidemiological estimates

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

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