The National Wastewater Surveillance System (NWSS): From inception to widespread coverage, 2020-2022, United States.

Wastewater surveillance is a valuable tool that can be used to track infectious diseases in a community. In September 2020, the Centers for Disease Control and Prevention (CDC) established the National Wastewater Surveillance System (NWSS) to coordinate and build the nation's capacity to detect and quantify concentrations of SARS-CoV-2 RNA in U.S. wastewater. This is the first surveillance summary of NWSS, covering September 1, 2020 to December 31, 2022. Through partnerships with state, tribal, local, and territorial health departments, NWSS became a national surveillance platform that can be readily expanded and adapted to meet changing public health needs. Beginning with 209 sampling sites in September 2020, NWSS rapidly expanded to >1500 sites by December 2022, covering ≈47 % of the U.S. population. As of December 2022, >152,000 unique wastewater samples have been collected by NWSS partners, primarily from wastewater treatment plants (WWTPs). WWTPs participating in NWSS tend to be larger than the average U.S. WWTP and serve more populated communities. In December 2022, ≈8 % of the nearly 16,000 U.S. WWTPs were participating in NWSS. NWSS partners used a variety of methods for sampling and testing wastewater samples; however, progress is being made to standardize these methods. In July 2021, NWSS partners started submitting SARS-CoV-2 genome sequencing data to NWSS. In October 2022, NWSS expanded to monkeypox virus testing, with plans to include additional infectious disease targets in the future. Through the rapid implementation and expansion of NWSS, important lessons have been learned. Wastewater surveillance programs should consider both surge and long-term capacities when developing an implementation plan, and early standardization of sampling and testing methods is important to facilitate data comparisons across sites. NWSS has proven to be a flexible and sustainable surveillance system that will continue to be a useful complement to case-based surveillance for guiding public health action.

The epidemiology of HIV population viral load in twelve sub-Saharan African countries.

BACKGROUND: We examined the epidemiology and transmission potential of HIV population viral load (VL) in 12 sub-Saharan African countries. METHODS: We analyzed data from Population-based HIV Impact Assessments (PHIAs), large national household-based surveys conducted between 2015 and 2019 in Cameroon, Cote d'Ivoire, Eswatini, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe. Blood-based biomarkers included HIV serology, recency of HIV infection, and VL. We estimated the number of people living with HIV (PLHIV) with suppressed viral load (<1,000 HIV-1 RNA copies/mL) and with unsuppressed viral load (viremic), the prevalence of unsuppressed HIV (population viremia), sex-specific HIV transmission ratios (number female incident HIV-1 infections/number unsuppressed male PLHIV per 100 persons-years [PY] and vice versa) and examined correlations between a variety of VL metrics and incident HIV. Country sample sizes ranged from 10,016 (Eswatini) to 30,637 (Rwanda); estimates were weighted and restricted to participants 15 years and older. RESULTS: The proportion of female PLHIV with viral suppression was higher than that among males in all countries, however, the number of unsuppressed females outnumbered that of unsuppressed males in all countries due to higher overall female HIV prevalence, with ratios ranging from 1.08 to 2.10 (median: 1.43). The spatial distribution of HIV seroprevalence, viremia prevalence, and number of unsuppressed adults often differed substantially within the same countries. The 1% and 5% of PLHIV with the highest VL on average accounted for 34% and 66%, respectively, of countries' total VL. HIV transmission ratios varied widely across countries and were higher for male-to-female (range: 2.3-28.3/100 PY) than for female-to-male transmission (range: 1.5-10.6/100 PY). In all countries mean log10 VL among unsuppressed males was higher than that among females. Correlations between VL measures and incident HIV varied, were weaker for VL metrics among females compared to males and were strongest for the number of unsuppressed PLHIV per 100 HIV-negative adults (R2 = 0.92). CONCLUSIONS: Despite higher proportions of viral suppression, female unsuppressed PLHIV outnumbered males in all countries examined. Unsuppressed male PLHIV have consistently higher VL and a higher risk of transmitting HIV than females. Just 5% of PLHIV account for almost two-thirds of countries' total VL. Population-level VL metrics help monitor the epidemic and highlight key programmatic gaps in these African countries.

Progress towards the UNAIDS 90-90-90 targets among persons aged 50 and older living with HIV in 13 African countries.

INTRODUCTION: Achieving optimal HIV outcomes, as measured by global 90-90-90 targets, that is awareness of HIV-positive status, receipt of antiretroviral (ARV) therapy among aware and viral load (VL) suppression among those on ARVs, respectively, is critical. However, few data from sub-Saharan Africa (SSA) are available on older people (50+) living with HIV (OPLWH). We examined 90-90-90 progress by age, 15-49 (as a comparison) and 50+ years, with further analyses among 50+ (55-59, 60-64, 65+ vs. 50-54), in 13 countries (Cameroon, Cote d'Ivoire, Eswatini, Ethiopia, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia and Zimbabwe). METHODS: Using data from nationally representative Population-based HIV Impact Assessments, conducted between 2015and 2019, participants from randomly selected households provided demographic and clinical information and whole blood specimens for HIV serology, VL and ARV testing. Survey weighted outcomes were estimated for 90-90-90 targets. Country-specific Poisson regression models examined 90-90-90 variation among OPLWH age strata. RESULTS: Analyses included 24,826 HIV-positive individuals (15-49 years: 20,170; 50+ years: 4656). The first, second and third 90 outcomes were achieved in 1, 10 and 5 countries, respectively, by those aged 15-49, while OPLWH achieved outcomes in 3, 13 and 12 countries, respectively. Among those aged 15-49, women were more likely to achieve 90-90-90 targets than men; however, among OPLWH, men were more likely to achieve first and third 90 targets than women, with second 90 achievement being equivalent. Country-specific 90-90-90 regression models among OPLWH demonstrated minimal variation by age stratum across 13 countries. Among OLPWH, no first 90 target differences were noted by age strata; three countries varied in the second 90 by older age strata but not in a consistent direction; one country showed higher achievement of the third 90 in an older age stratum. CONCLUSIONS: While OPLWH in these 13 countries were slightly more likely than younger people to be aware of their HIV-positive status (first 90), this target was not achieved in most countries. However, OPLWH achieved treatment (second 90) and VL suppression (third 90) targets in more countries than PLWH <50. Findings support expanded HIV testing, prevention and treatment services to meet ongoing OPLWH health needs in SSA.

Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa.

INTRODUCTION: HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups. METHODS: Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016-2018. RESULTS: Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty-eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city. CONCLUSIONS: The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.

Population-Based HIV Impact Assessments Survey Methods, Response, and Quality in Zimbabwe, Malawi, and Zambia.

BACKGROUND: The population-based HIV impact assessment (population-based HIV impact assessments) surveys are among the first to estimate national adult HIV incidence, subnational prevalence of viral load suppression, and pediatric HIV prevalence. We summarize the survey methods implemented in Zimbabwe, Malawi, and Zambia, as well as response rates and quality metrics. METHODS: Each cross-sectional, household-based survey used a 2-stage cluster design. Survey preparations included sample design, questionnaire development, tablet programming for informed consent and data collection, community mobilization, establishing a network of satellite laboratories, and fieldworker training. Interviewers collected demographic, behavioral, and clinical information using tablets. Blood was collected for home-based HIV testing and counseling (HBTC) and point-of-care CD4+ T-cell enumeration with results immediately returned. HIV-positive blood samples underwent laboratory-based confirmatory testing, HIV incidence testing, RNA polymerase chain reaction (viral load), DNA polymerase chain reaction (early infant diagnosis), and serum antiretroviral drug detection. Data were weighted for survey design, and chi square automatic interaction detection-based methods were used to adjust for nonresponse. RESULTS: Each survey recruited a nationally representative, household-based sample of children and adults over a 6-10-month period in 2015 and 2016. Most (84%-90%) of the 12,000-14,000 eligible households in each country participated in the survey, with 77%-81% of eligible adults completing an interview and providing blood for HIV testing. Among eligible children, 59%-73% completed HIV testing. Across the 3 surveys, 97.8% of interview data were complete and had no errors. CONCLUSION: Conducting a national population-based HIV impact assessment with immediate return of HIV and other point-of-care test results was feasible, and data quality was high.

Coronavirus Disease 2019 (COVID-19) Mitigation Efforts and Testing During an In-Person Training Event-Uganda, 12-29 October 2020.

Large public-health training events may result in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Universal SARS-CoV-2 testing during trainings for the Uganda Population-based HIV Impact Assessment identified 28 of 475 (5.9%) individuals with coronavirus disease 2019 (COVID-19) among attendees; most (89.3%) were asymptomatic. Until COVID-19 vaccine is readily available for staff and participants, effective COVID-19 mitigation measures, along with SARS-CoV-2 testing, are recommended for in-person trainings, particularly when trainees will have subsequent contact with survey participants.

Using geographical analysis to identify child health inequality in sub-Saharan Africa.

One challenge to achieving Millennium Development Goals was inequitable access to quality health services. In order to achieve the Sustainable Development Goals, interventions need to reach underserved populations. Analyzing health indicators in small geographic units aids the identification of hotspots where coverage lags behind neighboring areas. The purpose of these analyses is to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions. We calculated Global Moran's I statistics and used Local Indicator of Spatial Association analysis to produce a spatial layer showing spatial associations. We created maps to visualize sub-national autocorrelation and spatial clusters. The Global Moran's I statistic was positive for each indicator (range: 0.41 to 0.68), and statistically significant (p <0.05), suggesting spatial autocorrelation across national borders, and highlighting the need to examine health indicators both across countries and within them. Patterns of substantial differences among contiguous subareas were apparent; the average intra-country difference for each indicator exceeded 20 percentage points. Clusters of cross-border associations were also apparent, facilitating the identification of hotspots and informing the allocation of resources to reduce child health inequity between and within countries. This study exposes differences in health indicators in contiguous geographic areas, indicating that specific regional and subnational, in addition to national, strategies to improve health and reduce health inequalities are warranted.

Status of HIV Epidemic Control Among Adolescent Girls and Young Women Aged 15-24 Years - Seven African Countries, 2015-2017.

In 2016, an estimated 1.5 million females aged 15-24 years were living with human immunodeficiency virus (HIV) infection in Eastern and Southern Africa, where the prevalence of HIV infection among adolescent girls and young women (3.4%) is more than double that for males in the same age range (1.6%) (1). Progress was assessed toward the Joint United Nations Programme on HIV/AIDS (UNAIDS) 2020 targets for adolescent girls and young women in sub-Saharan Africa (90% of those with HIV infection aware of their status, 90% of HIV-infected persons aware of their status on antiretroviral treatment [ART], and 90% of those on treatment virally suppressed [HIV viral load <1,000 HIV RNA copies/mL]) (2) using data from recent Population-based HIV Impact Assessment (PHIA) surveys in seven countries. The national prevalence of HIV infection in adolescent girls and young women aged 15-24 years, the percentage who were aware of their status, and among those persons who were aware, the percentage who had achieved viral suppression were calculated. The target for viral suppression among all persons with HIV infection is 73% (the product of 90% x 90% x 90%). Among all seven countries, the prevalence of HIV infection among adolescent girls and young women was 3.6%; among those in this group, 46.3% reported being aware of their HIV-positive status, and 45.0% were virally suppressed. Sustained efforts by national HIV and public health programs to diagnose HIV infection in adolescent girls and young women as early as possible to ensure rapid initiation of ART should help achieve epidemic control among adolescent girls and young women.

A country bug in the city: urban infestation by the Chagas disease vector Triatoma infestans in Arequipa, Peru.

BACKGROUND: Interruption of vector-borne transmission of Trypanosoma cruzi remains an unrealized objective in many Latin American countries. The task of vector control is complicated by the emergence of vector insects in urban areas. METHODS: Utilizing data from a large-scale vector control program in Arequipa, Peru, we explored the spatial patterns of infestation by Triatoma infestans in an urban and peri-urban landscape. Multilevel logistic regression was utilized to assess the associations between household infestation and household- and locality-level socio-environmental measures. RESULTS: Of 37,229 households inspected for infestation, 6,982 (18.8%; 95% CI: 18.4 - 19.2%) were infested by T. infestans. Eighty clusters of infestation were identified, ranging in area from 0.1 to 68.7 hectares and containing as few as one and as many as 1,139 infested households. Spatial dependence between infested households was significant at distances up to 2,000 meters. Household T. infestans infestation was associated with household- and locality-level factors, including housing density, elevation, land surface temperature, and locality type. CONCLUSIONS: High levels of T. infestans infestation, characterized by spatial heterogeneity, were found across extensive urban and peri-urban areas prior to vector control. Several environmental and social factors, which may directly or indirectly influence the biology and behavior of T. infestans, were associated with infestation. Spatial clustering of infestation in the urban context may both challenge and inform surveillance and control of vector reemergence after insecticide intervention.

Use of Individual-level Covariates to Improve Latent Class Analysis of Trypanosoma Cruzi Diagnostic Tests.

Statistical methods such as latent class analysis can estimate the sensitivity and specificity of diagnostic tests when no perfect reference test exists. Traditional latent class methods assume a constant disease prevalence in one or more tested populations. When the risk of disease varies in a known way, these models fail to take advantage of additional information that can be obtained by measuring risk factors at the level of the individual. We show that by incorporating complex field-based epidemiologic data, in which the disease prevalence varies as a continuous function of individual-level covariates, our model produces more accurate sensitivity and specificity estimates than previous methods. We apply this technique to a simulated population and to actual Chagas disease test data from a community near Arequipa, Peru. Results from our model estimate that the first-line enzyme-linked immunosorbent assay has a sensitivity of 78% (95% CI: 62-100%) and a specificity of 100% (95% CI: 99-100%). The confirmatory immunofluorescence assay is estimated to be 73% sensitive (95% CI: 65-81%) and 99% specific (95% CI: 96-100%).

A history of chagas disease transmission, control, and re-emergence in peri-rural La Joya, Peru.

BACKGROUND: The history of Chagas disease control in Peru and many other nations is marked by scattered and poorly documented vector control campaigns. The complexities of human migration and sporadic control campaigns complicate evaluation of the burden of Chagas disease and dynamics of Trypanosoma cruzi transmission. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a cross-sectional serological and entomological study to evaluate temporal and spatial patterns of T. cruzi transmission in a peri-rural region of La Joya, Peru. We use a multivariate catalytic model and Bayesian methods to estimate incidence of infection over time and thereby elucidate the complex history of transmission in the area. Of 1,333 study participants, 101 (7.6%; 95% CI: 6.2-9.0%) were confirmed T. cruzi seropositive. Spatial clustering of parasitic infection was found in vector insects, but not in human cases. Expanded catalytic models suggest that transmission was interrupted in the study area in 1996 (95% credible interval: 1991-2000), with a resultant decline in the average annual incidence of infection from 0.9% (95% credible interval: 0.6-1.3%) to 0.1% (95% credible interval: 0.005-0.3%). Through a search of archival newspaper reports, we uncovered documentation of a 1995 vector control campaign, and thereby independently validated the model estimates. CONCLUSIONS/SIGNIFICANCE: High levels of T. cruzi transmission had been ongoing in peri-rural La Joya prior to interruption of parasite transmission through a little-documented vector control campaign in 1995. Despite the efficacy of the 1995 control campaign, T. cruzi was rapidly reemerging in vector populations in La Joya, emphasizing the need for continuing surveillance and control at the rural-urban interface.