A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.</p

Which delivery model innovations can support sustainable HIV treatment?

The rapid scale-up of antiretroviral treatment (ART) for HIV since the mid-2000s, mostly through disease-specific or “vertical” programmes, has been a highly successful undertaking, which averted millions of deaths and prevented many new infections. However, the dynamics of the HIV epidemic and changing political and financial commitment to fight the disease will likely require new models for the delivery of ART over the coming decades if the promises of universal treatment are to be met. Delivery model innovations for ART are intended to improve both the effectiveness and efficiency of the HIV treatment cascade, reaching new people who require ART and providing ART to more people without an increase in resources. We describe twelve models for ART delivery, which could be achieved through five categories of delivery innovations: integrating ART (“vertical ART plus”, “partially-integrated ART” and “fully-integrated ART”); modifying steps in the ART value chain (“professional task-shifted ART”, “people task-shifted ART” and “technology-supported ART”); eliminating steps in the ART value chain (“immediate ART” and “less frequent ART pick-up”); changing ART locations (“private-sector ART”, “traditional-sector ART” and “ART outside the health sector”); and keeping the status quo (“vertical ART”). The different delivery model innovations are not mutually exclusive and several could be combined, such as “vertical ART plus” with “task-shifted ART”. Suitability of the models will highly depend on local and national contexts, including existing health systems resources, available funding, and type of HIV epidemic. Future implementation research needs to identify which models are the best fit for different contexts

COVID-19 antibody responses in individuals with natural immunity and with vaccination-induced immunity:a systematic review and meta-analysis

Background: The COVID-19 pandemic has caused a large mortality and morbidity burden globally. For individuals, a strong immune response is the most effective means to block SARS-CoV-2 infection. To inform clinical case management of COVID-19, development of improved vaccines, and public health policy, a better understanding of antibody response dynamics and duration following SARS-CoV-2 infection and after vaccination is imperatively needed. Methods: We systematically analyzed antibody response rates in naturally infected COVID-19 patients and vaccinated individuals. Specifically, we searched all published and pre-published literature between 1 December 2019 and 31 July 2023 using MeSH terms and “all field” terms comprising “COVID-19” or “SARS-CoV-2,” and “antibody response” or “immunity response” or “humoral immune.” We included experimental and observational studies that provided antibody positivity rates following natural COVID-19 infection or vaccination. A total of 44 studies reporting antibody positivity rate changes over time were included. Results: The meta-analysis showed that within the first week after COVID-19 symptom onset/diagnosis or vaccination, antibody response rates in vaccinated individuals were lower than those in infected patients (p &lt; 0.01), but no significant difference was observed from the second week to the sixth month. IgG, IgA, and IgM positivity rates increased during the first 3 weeks; thereafter, IgG positivity rates were maintained at a relatively high level, while the IgM seroconversion rate dropped. Conclusions: Antibody production following vaccination might not occur as quickly or strongly as after natural infection, and the IgM antibody response was less persistent than the IgG response.</p

Mapping and characterising areas with high levels of HIV transmission in sub-Saharan Africa: A geospatial analysis of national survey data

BACKGROUND: In the generalised epidemics of sub-Saharan Africa (SSA), human immunodeficiency virus (HIV) prevalence shows patterns of clustered micro-epidemics. We mapped and characterised these high-prevalence areas for young adults (15-29 years of age), as a proxy for areas with high levels of transmission, for 7 countries in Eastern and Southern Africa: Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe. METHODS AND FINDINGS: We used geolocated survey data from the most recent United States Agency for International Development (USAID) demographic and health surveys (DHSs) and AIDS indicator surveys (AISs) (collected between 2008-2009 and 2015-2016), which included about 113,000 adults-of which there were about 53,000 young adults (27,000 women, 28,000 men)-from over 3,500 sample locations. First, ordinary kriging was applied to predict HIV prevalence at unmeasured locations. Second, we explored to what extent behavioural, socioeconomic, and environmental factors explain HIV prevalence at the individual- and sample-location level, by developing a series of multilevel multivariable logistic regression models and geospatially visualising unexplained model heterogeneity. National-level HIV prevalence for young adults ranged from 2.2% in Tanzania to 7.7% in Mozambique. However, at the subnational level, we found areas with prevalence among young adults as high as 11% or 15% alternating with areas with prevalence between 0% and 2%, suggesting the existence of areas with high levels of transmission Overall, 15.6% of heterogeneity could be explained by an interplay of known behavioural, socioeconomic, and environmental factors. Maps of the interpolated random effect estimates show that environmental variables, representing indicators of economic activity, were most powerful in explaining high-prevalence areas. Main study limitations were the inability to infer causality due to the cross-sectional nature of the surveys and the likely under-sampling of key populations in the surveys. CONCLUSIONS: We found that, among young adults, micro-epidemics of relatively high HIV prevalence alternate with areas of very low prevalence, clearly illustrating the existence of areas with high levels of transmission. These areas are partially characterised by high economic activity, relatively high socioeconomic status, and risky sexual behaviour. Localised HIV prevention interventions specifically tailored to the populations at risk will be essential to curb transmission. More fine-scale geospatial mapping of key populations,-such as sex workers and migrant populations-could help us further understand the drivers of these areas with high levels of transmission and help us determine how they fuel the generalised epidemics in SSA

HIV prevalence among men who have sex with men, transgender women and cisgender male sex workers in sub‐Saharan Africa: a systematic review and meta‐analysis

Introduction Developing effective targets, policies and services for key populations requires estimations of population sizes and HIV prevalence across countries and regions. We estimated the relative and absolute HIV prevalence among men who have sex with men (MSM), transgender women and men, and male and transgender sex workers (MSW and TGSW) in sub-Saharan African countries using peer-reviewed literature. Methods We performed a systematic review of peer-reviewed studies assessing HIV prevalence in MSM, transgender women and men, MSW and TGSW in sub-Saharan Africa between 2010 and 2021, following PRISMA guidelines. We searched Embase, Medline Epub, Africa Index Medicus, Africa Journal Online, Web of Science and Google Scholar. We calculated HIV prevalence ratios (PRs) between the study prevalence, and the geospatial-, sex, time and age-matched general population prevalence. We extrapolated results for MSM and transgender women to estimate HIV prevalence and the number living with HIV for each country in sub-Saharan Africa using pooled review results, and regression approximations for countries with no peer-reviewed data. Results and discussion We found 44 articles assessing HIV prevalence in MSM, 10 in transgender women, five in MSW and zero in transgender men and TGSW. Prevalence among MSM and transgender women was significantly higher compared to the general population: PRs of 11.3 [CI: 9.9–12.9] for MSM and 8.1 [CI: 6.9–9.6] for transgender women in Western and Central Africa, and, respectively, 1.9 [CI: 1.7–2.0] and 2.1 [CI: 1.9–2.4] in Eastern and Southern Africa. Prevalence among MSW was significantly higher in both Nigeria (PR: 12.4 [CI: 7.3–21.0]) and Kenya (PR: 8.6 [CI: 4.6–15.6]). Extrapolating our findings for MSM and transgender women resulted in an estimated HIV prevalence of 15% or higher for about 60% of all sub-Saharan African countries for MSM, and for all but two countries for transgender women. Conclusions HIV prevalence among MSM and transgender women throughout sub-Saharan Africa is alarmingly high. This high prevalence, coupled with the specific risks and vulnerabilities faced by these populations, highlights the urgent need for risk-group-tailored prevention and treatment interventions across the sub-continent. There is a clear gap in knowledge on HIV prevalence among transgender men, MSW and TGSW in sub-Saharan Africa

Visceral leishmaniasis: Spatiotemporal heterogeneity and drivers underlying the hotspots in Muzaffarpur, Bihar, India

Background: Despite the overall decrease in visceral leishmaniasis (VL) incidence on the Indian subcontinent, there remain spatiotemporal clusters or ‘hotspots’ of new cases. The characteristics of these hotspots, underlying transmission dynamics, and their importance for shaping control strategies are not yet fully understood and are investigated in this study for a VL endemic area of ~100,000 inhabitants in Bihar, India between 2007–2015. Methodology/Principal findings VL incidence (cases/10,000/year) dropped from 12.3 in 2007 to 0.9 in 2015, which is just below the World Health Organizations’ threshold for elimination as a public health problem. Clustering of VL was assessed between subvillages (hamlets), using multiple geospatial and (spatio)temporal autocorrelation and hotspot analyses. One to three hotspots were identified each year, often persisting for 1–5 successive years with a modal radius of ~500m. The relative risk of having VL was 5–86 times higher for inhabitants of hotspots, compared to those living outside hotspots. Hotspots harbour significantly more households from the two lowest asset quintiles (as proxy for socio-economic status). Overall, children and young adelescents (5–14 years) have the highest risk for VL, but within hotspots and at the start of outbreaks, older age groups (35+ years) show a comparable high risk. Conclusions/Significance: This study demonstrates significant spatiotemporal heterogeneity in VL incidence at subdistrict level. The association between poverty and hotspots confirms that VL is a disease of ‘the poorest of the poor’ and age patterns suggest a potential role of waning immunity as underlying driver of hotspots. The recommended insecticide spraying radius of 500m around detected VL cases corresponds to the modal hotspot radius found in this study. Additional data on immunity and asymptomatic infection, and the development of spatiotemporally explicit transmission models that simulate hotspot dynamics and predict the impact of interventions at the smaller geographical scale will be crucial tools in sustaining elimination

A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases

A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design.

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases

Visceral leishmaniasis: Spatiotemporal heterogeneity and drivers underlying the hotspots in Muzaffarpur, Bihar, India

BACKGROUND: Despite the overall decrease in visceral leishmaniasis (VL) incidence on the Indian subcontinent, there remain spatiotemporal clusters or 'hotspots' of new cases. The characteristics of these hotspots, underlying transmission dynamics, and their importance for shaping control strategies are not yet fully understood and are investigated in this study for a VL endemic area of ~100,000 inhabitants in Bihar, India between 2007-2015. METHODOLOGY/PRINCIPAL FINDINGS: VL incidence (cases/10,000/year) dropped from 12.3 in 2007 to 0.9 in 2015, which is just below the World Health Organizations' threshold for elimination as a public health problem. Clustering of VL was assessed between subvillages (hamlets), using multiple geospatial and (spatio)temporal autocorrelation and hotspot analyses. One to three hotspots were identified each year, often persisting for 1-5 successive years with a modal radius of ~500m. The relative risk of having VL was 5-86 times higher for inhabitants of hotspots, compared to those living outside hotspots. Hotspots harbour significantly more households from the two lowest asset quintiles (as proxy for socio-economic status). Overall, children and young adelescents (5-14 years) have the highest risk for VL, but within hotspots and at the start of outbreaks, older age groups (35+ years) show a comparable high risk. CONCLUSIONS/SIGNIFICANCE: This study demonstrates significant spatiotemporal heterogeneity in VL incidence at subdistrict level. The association between poverty and hotspots confirms that VL is a disease of 'the poorest of the poor' and age patterns suggest a potential role of waning immunity as underlying driver of hotspots. The recommended insecticide spraying radius of 500m around detected VL cases corresponds to the modal hotspot radius found in this study. Additional data on immunity and asymptomatic infection, and the development of spatiotemporally explicit transmission models that simulate hotspot dynamics and predict the impact of interventions at the smaller geographical scale will be crucial tools in sustaining elimination