Prevalence and Correlation Analysis of Soil-Transmitted Helminths Infections and Treatment Coverage for Preschool and School Aged Children in Kenya: Secondary Analysis of the National School Based Deworming Program Data

Background: Soil-transmitted helminths (STH) are among the most common parasitic infections globally, disproportionately affecting children. Treatment of STH in Kenya is often targeted at preschool (PSAC) and school aged (SAC) children delivered through annual mass drug administration (MDA) in primary schools. Understanding group-specific prevalence and dynamics between treatment and coverage is critical for continued treatment success. This study aims to provide detailed information on group-specific infection prevalence and relative reductions (RR), and their relationships with treatment coverage over time. Additionally, it aims to quantify the correlation between the observed school level infection prevalence and treatment coverage. Methods: Secondary analysis of existing data collected between 2012 and 2018 by the monitoring and evaluation (M&E) program of the National School-Based Deworming (NSBD) program was used. The M&E program conducted surveys utilizing cross-sectional study design, at four survey time points, in a nationally-representative sample of schoolchildren across counties in Kenya. In each participating school, the program randomly sampled 108 children per school, of both groups. Infection prevalence was estimated using binomial regression, RR in prevalence using multivariable mixed effects model, statistical correlations using structural equation modeling, and change-point-analysis using the binary segmentation algorithm. Results: Overall, STH prevalence for PSAC was 33.7, 20.2, 19.0, and 17.9% during Year 1 (Y1), Year 3 (Y3), Year 5 (Y5), and Year 6 (Y6) surveys, respectively with an overall RR of 46.9% (p = 0.001) from Y1 to Y6. Similarly, overall STH prevalence for SAC was 33.6, 18.4, 14.7, and 12.5% during Y1, Y3, Y5, and Y6 surveys, respectively with an overall RR of 62.6% (p < 0.001). An overall (all time points) significant but very weak negative correlation was found between treatment coverage and undifferentiated STH prevalence (r = -0.144, p = 0.002) among PSAC but not in SAC. Further, we observed inter-county heterogeneity variation in infection prevalence, RR, as well as correlations. Conclusion: The analysis showed that after six rounds of MDA, prevalence of STH has significantly declined among both groups of children, however not to a point where it is not a public health problem (below 1%). The analysis, additionally established an overall significant but weak negative correlation between treatment coverage and prevalence, indicating that the current treatment coverage might not be sufficient to drive the overall STH prevalence to below 1%. These findings will allow STH control programs in Kenya to make decisions that will accelerate the attainment of STH elimination as a public health problem

Using a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya

BackgroundInfections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH).MethodsA cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates.ResultsThe overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and&lt; 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and&lt; 1%, that of 20 counties estimated to be between 1% and&lt; 10%, that of two counties estimated to be between 10% and&lt; 20%, and that of one county estimated to be between 20% and&lt; 50%.ConclusionSCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and&lt; 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is&lt; 1%

The Role of Wastewater Testing for SARS-CoV-2 Surveillance

Wastewater testing for SARS-CoV-2 is relatively new; however, it builds on existing public health surveillance infrastructure. There is a limited but growing evidence base for its use, despite notable interpretation challenges. Wastewater testing results have helped to inform public health policy and interventions during the COVID-19 pandemic in Ontario and other jurisdictions. Wastewater testing for SARS-CoV-2 is useful for early detection of outbreaks and surges as well as population-wide surveillance of COVID-19 that is complementary to clinical testing. Further, it offers an efficient means of SARS-CoV-2 surveillance for specific settings such as correctional facilities, shelters, and university residences. Wastewater testing can also be used for the detection and monitoring of variants of concern (VOCs)

Neonatal mortality and inequalities in Bangladesh: differential progress and sub-national developments

A rapid reduction in under-five mortality has put Bangladesh on-track to reach Millennium Development Goal 4. Little research, however, has been conducted into neonatal reductions and sub-national rates in the country, with considerable disparities potentially masked by national reductions. The aim of this paper is to estimate national and sub-national rates of neonatal mortality to compute relative and absolute inequalities between sub-national groups and draw comparisons with rates of under-five mortality. Mortality rates for under-five children and neonates were estimated directly for 1980–1981 to 2010–2011 using data from six waves of the Demographic and Health Survey. Rates were stratified by levels of rural/urban location, household wealth and maternal education. Absolute and relative inequalities within these groups were measured by rate differences and ratios, and where possible, slope and relative indices of inequality. National mortality was shown to have decreased dramatically although at differential rates for under-fives and neonates. Across all equity markers, a general pattern of declining absolute but constant relative inequalities was found. For mortality rates stratified by education and wealth mixed evidence suggests that relative inequalities may have also fallen. Although disparities remain, Bangladesh has achieved a rare combination of substantive reductions in mortality levels without increases in relative inequalities. A coalescence of substantial increases in coverage and equitable distribution of key child and neonatal interventions with widespread health sectoral and policy changes over the last 30 years may in part explain this exceptional pattern

Opportunities for improved HIV prevention and treatment through budget optimization in Eswatini.

IntroductionEswatini achieved a 44% decrease in new HIV infections from 2014 to 2019 through substantial scale-up of testing and treatment. However, it still has one of the highest rates of HIV incidence in the world, with 14 infections per 1,000 adults 15-49 years estimated for 2017. The Government of Eswatini has called for an 85% reduction in new infections by 2023 over 2017 levels. To make further progress towards this target and to achieve maximum health gains, this study aims to model optimized investments of available HIV resources.MethodsThe Optima HIV model was applied to estimate the impact of efficiency strategies to accelerate prevention of HIV infections and HIV-related deaths. We estimated the number of infections and deaths that could be prevented by optimizing HIV investments. We optimize across HIV programs, then across service delivery modalities for voluntary medical male circumcision (VMMC), HIV testing, and antiretroviral refill, as well as switching to a lower cost antiretroviral regimen.FindingsUnder an optimized budget, prioritising HIV testing for the general population followed by key preventative interventions may result in approximately 1,000 more new infections (2% more) being averted by 2023. More infections could be averted with further optimization between service delivery modalities across the HIV cascade. Scaling-up index and self-testing could lead to 100,000 more people getting tested for HIV (25% more tests) with the same budget. By prioritizing Fast-Track, community-based, and facility-based antiretroviral refill options, an estimated 30,000 more people could receive treatment, 17% more than baseline or US$5.5 million could be saved, 4$4.5 million (7% of total budget) and US$6.6 million (10% of total budget) could be saved, respectively.SignificanceWith a relatively short five-year timeframe, even under a substantially increased and optimized budget, Eswatini is unlikely to reach their ambitious national prevention target by 2023. However, by optimizing investment of the same budget towards highly cost-effective VMMC, testing, and treatment modalities, further reductions in HIV incidence and cost savings could be realized

Cost-effectiveness and impact of pre-exposure prophylaxis to prevent HIV among men who have sex with men in Asia: A modelling study.

IntroductionMore than 70% of new HIV infections in Asia occurred in eight countries in 2020: Cambodia, China, India, Indonesia, Myanmar, Nepal, Thailand, and Vietnam-with a rising incidence among men who have sex with men (MSM). The World Health Organization (WHO) recommends pre-exposure prophylaxis (PrEP) for those at risk of acquiring HIV, yet wide-scale implementation of PrEP, on a daily or event-driven basis, has been limited in Asia.MethodsThe Optima HIV model was applied to examine the impact of scaling-up PrEP over five-years to cover an additional 15% of MSM compared with baseline coverage, a target deemed feasible by regional experts. Based on behavioral survey data, we assume that covering 15% of higher-risk MSM will cover 30% of all sexual acts in this group. Scenarios to compare the impact of generic-brand daily dosing of PrEP with generic event-driven dosing (15 days a month) were modelled from the start of 2022 to the end of 2026. Cost-effectiveness of generic versus branded PrEP was also assessed for China, the only country with an active patent for branded, higher cost PrEP. The impact on new HIV infections among the entire population and cost per HIV-related disability-adjusted life year (DALY) averted were estimated from the beginning of 2022 to the end of 2031 and from 2022 to 2051.ResultsIf PrEP were scaled-up to cover an additional 15% of MSM engaging in higher-risk behavior from the beginning of 2022 to the end of 2026 in the eight Asian countries considered, an additional 100,000 (66,000-130,000) HIV infections (17%) and 300,000 (198,000-390,000) HIV-related DALYs (3%) could be averted over the 2022 to 2031 period. The estimated cost per HIV-related DALY averted from 2022 to 2031 ranged from US$600 for event-driven generic PrEP in Indonesia to US$34,400 for daily branded PrEP in Thailand. Over a longer timeframe from 2022 to 2051, the cost per HIV-related DALY averted could be reduced to US$100-US$12,700.ConclusionPrEP is a critical tool to further reduce HIV incidence in highly concentrated epidemics. Implementing PrEP in Asia may be cost-effective in settings with increasing HIV prevalence among MSM and if PrEP drug costs can be reduced, PrEP could be more cost-effective over longer timeframes

Using a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya

Background: Infections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH). Methods: A cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates. Results: The overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and< 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and< 1%, that of 20 counties estimated to be between 1% and< 10%, that of two counties estimated to be between 10% and< 20%, and that of one county estimated to be between 20% and< 50%. Conclusion: SCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and< 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is< 1%

Model-based geostatistical design and analysis of prevalence for soil-transmitted helminths in Kenya:Results from ten-years of the Kenya national school-based deworming programme

Background Kenya is endemic for soil-transmitted helminths (STH) with over 6 million children in 27 counties currently at-risk. A national school-based deworming programme (NSBDP) was launched in 2012 with a goal to eliminate parasitic worms as a public health problem. This study used model-based geostatistical (MBG) approach to design and analyse the impact of the NSBDP and inform treatment strategy changes. Methods A cross-sectional study was used to survey 200 schools across 27 counties in Kenya. The study design, school selection and analysis followed the MBG approach which incorporated historical data on treatment, morbidity and environmental covariates to efficiently predict the helminths prevalence in Kenya. Results Overall, the NSBDP geographic area prevalence for any STH was estimated to sit between 2 % and 0.999. Species-specific thresholds were between 2 % and 0.999. Conclusions Based on the World Health Organization guidelines, STH treatment requirements can now be confidently refined. Ten counties may consider suspending treatment and implement appropriate surveillance system, while another 10 will require treatment once every two years, and the remaining seven will require treatment once every year

Model-Based Geostatistical Methods Enable Efficient Design and Analysis of Prevalence Surveys for Soil-Transmitted Helminth Infection and Other Neglected Tropical Diseases

Maps of the geographical variation in prevalence play an important role in large-scale programs for the control of neglected tropical diseases. Precontrol mapping is needed to establish the appropriate control intervention in each area of the country in question. Mapping is also needed postintervention to measure the success of control efforts. In the absence of comprehensive disease registries, mapping efforts can be informed by 2 kinds of data: empirical estimates of local prevalence obtained by testing individuals from a sample of communities within the geographical region of interest, and digital images of environmental factors that are predictive of local prevalence. In this article, we focus on the design and analysis of impact surveys, that is, prevalence surveys that are conducted postintervention with the aim of informing decisions on what further intervention, if any, is needed to achieve elimination of the disease as a public health problem. We show that geospatial statistical methods enable prevalence surveys to be designed and analyzed as efficiently as possible so as to make best use of hard-won field data. We use 3 case studies based on data from soil-transmitted helminth impact surveys in Kenya, Sierra Leone, and Zimbabwe to compare the predictive performance of model-based geostatistics with methods described in current World Health Organization (WHO) guidelines. In all 3 cases, we find that model-based geostatistics substantially outperforms the current WHO guidelines, delivering improved precision for reduced field-sampling effort. We argue from experience that similar improvements will hold for prevalence mapping of other neglected tropical diseases