Environmental cleaning is essential to patient and health worker safety, yet it is a substantially neglected area in terms of knowledge, practice, and capacity-building, especially in resource-limited settings. Public health advocacy, research and investment are urgently needed to develop and implement cost-effective interventions to improve environmental cleanliness and, thus, overall healthcare quality and safety. We outline here the CLEAN Group Consensus exercise yielding twelve urgent research questions, grouped into four thematic areas: standards, system strengthening, behaviour change, and innovation.

BACKGROUND: Data on awareness of HIV status among people living with HIV (PLHIV) are critical to estimating progress toward epidemic control. To ascertain the accuracy of self-reported HIV status and antiretroviral drug (ARV) use in the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), we compared self-reported HIV status with HIV rapid diagnostic test (RDT) results and self-reported ARV use with detectable blood ARV levels. METHODS: On the basis of responses and test results, participants were categorized by HIV status and ARV use. Self-reported HIV status and ARV use performance characteristics were determined by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Proportions and other analyses were weighted to account for complex survey design. RESULTS: During NAIIS, 186,405 participants consented for interview out of which 58,646 reported knowing their HIV status. Of the 959 (weighted, 1.5%) who self-reported being HIV-positive, 849 (92.1%) tested HIV positive and 64 (7.9%) tested HIV negative via RDT and polymerase chain reaction test for discordant positive results. Of the 849 who tested HIV positive, 743 (89.8%) reported using ARV and 72 (10.2%) reported not using ARV. Of 57,687 who self-reported being HIV negative, 686 (1.2%) tested HIV positive via RDT, with ARV biomarkers detected among 195 (25.1%). ARV was detected among 94.5% of those who self-reported using ARV and among 42.0% of those who self-reported not using ARV. Overall, self-reported HIV status had sensitivity of 52.7% (95% confidence interval [CI]: 49.4%-56.0%) with specificity of 99.9% (95% CI: 99.8%-99.9%). Self-reported ARV use had sensitivity of 95.2% (95% CI: 93.6%-96.7%) and specificity of 54.5% (95% CI: 48.8%-70.7%). CONCLUSIONS: Self-reported HIV status and ARV use screening tests were found to be low-validity measures during NAIIS. Laboratory tests to confirm self-reported information may be necessary to determine accurate HIV and clinical status for HIV studies in Nigeria.

BACKGROUND: As of October 2021, 47 (80%) of the 59 countries, identified at highest risk for Maternal and Neonatal Tetanus (MNT), had been validated for elimination. We assessed sustainability of MNT elimination (MNTE) in 28 countries that were validated during 2011‒2020. METHODS: We assessed the attainment of the following MNTE sustainability indicators: 1) ≥ 90% coverage with three doses of Diphtheria-Tetanus-Pertussis vaccine (DTP3) among infants < 1 year, 2) ≥ 80% coverage with at least two doses of tetanus toxoid-containing vaccine (TTCV2 +) among pregnant women, 3) ≥ 80% protection at birth (PAB), 4) ≥ 70% skilled birth attendance (SBA), and 4) ≥ 80% first (ANC1) and fourth antenatal care (ANC4) visits. We assessed the introduction of TTCV booster doses. Data sources included the 2020 WHO /UNICEF Joint Reporting Forms, and the latest Demographic and Health Survey (DHS) or Multi-Indicator Cluster Surveys (MICS) for each country, if available. We reviewed literature and used DHS/MICS data to identify barriers to sustaining MNTE. RESULTS: Of 28 assessed countries, 7 (25%) reported ≥ 90% DTP3 coverage, 4 of 26 (16%) reported ≥ 80% TTCV2 + coverage, and 23 of 27 (85%) reported ≥ 80% PAB coverage. Based on DHS/MICS in 15 of the 28 countries, 10 (67%) achieved ≥ 70% SBA delivery, 13 (87%) achieved ≥ 80% ANC1 visit coverage, and 3 (20%) ≥ 80% ANC4 visit coverage. We observed sub-optimal coverage in many countries at the subnational level. The first, second and third booster doses of TTCV respectively have been introduced in 6 (21%), 5 (18%), and 1 (4%) of 28 countries. Only three countries conducted post-MNTE validation assessments. Barriers to MNTE sustainability included: competing program priorities, limited resources to introduce TTCV booster doses and implement corrective immunization in high-risk districts and socio-economic factors. CONCLUSIONS: Despite good performance of MNTE indicators in several countries, MNTE sustainability appears threatened in some countries. Integration and coordination of MNTE activities with other immunization activities in the context of the Immunization Agenda 2030 lifecourse vaccination strategy such as providing tetanus booster doses in school-based vaccination platforms, during measles second dose and HPV vaccination, and integrating MNTE post-validation assessments with immunization program reviews will ensure MNTE is sustained.

BACKGROUND: Ineffective linkage to care (LTC) is a known challenge for community HIV testing. To overcome this challenge, a robust linkage to care strategy was adopted by the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). The NAIIS linkage to care strategy was further adapted to improve Nigeria's programmatic efforts to achieve the 1st 90 as part of the Nigeria Antiretroviral Therapy (ART) Surge initiative, which also included targeted community testing. In this paper we provide an overview of the NAIIS LTC strategy and describe the impact of this strategy on both the NAIIS and the Surge initiatives. METHODS: The NAIIS collaborated with community-based organizations (CBOs) and deployed mobile health (mHealth) technology with real-time dashboards to manage and optimize community LTC for people living with HIV (PLHIV) diagnosed during the survey. In NAIIS, CBOs' role was to facilitate linkage of identified PLHIV in community to facility of their choice. For the ART Surge, we modified the NAIIS LTC strategy by empowering both CBOs and mobile community teams as responsible for not only active LTC but also for community testing, ART initiation, and retention in care. RESULTS: Of the 2,739 PLHIV 15 years and above identified in NAIIS, 1,975 (72.1%) were either unaware of their HIV-positive status (N = 1890) or were aware of their HIV-positive status but not receiving treatment (N = 85). Of these, 1,342 (67.9%) were linked to care, of which 952 (70.9%) were initiated on ART. Among 1,890 newly diagnosed PLHIV, 1,278 (67.6%) were linked to care, 33.7% self-linked and 66.3% were linked by CBOs. Among 85 known PLHIV not on treatment, 64 (75.3%) were linked; 32.8% self-linked and 67.2% were linked by a CBO. In the ART Surge, LTC and treatment initiation rates were 98% and 100%, respectively. Three-month retention for monthly treatment initiation cohorts improved from 76% to 90% over 6 months. CONCLUSIONS: Active LTC strategies by local CBOs and mobile community teams improved LTC and ART initiation in the ART Surge initiative. The use of mHealth technology resulted in timely and accurate documentation of results in NAIIS. By deploying mHealth in addition to active LTC, CBOs and mobile community teams could effectively scale up ART with real-time documentation of client-level outcomes.

PURPOSE: The 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) showed Nigeria's progress toward the UNAIDS 90-90-90 targets: 47% of HIV-positive individuals knew their status; of these, 96% were receiving antiretroviral therapy (ART); and of these, 81% were virally suppressed. To improve identification of HIV-positive individuals, Nigeria developed an Enhanced Community Case-Finding Package (ECCP). We describe ECCP implementation in nine states and assess its effect. METHODS: ECCP included four core strategies (small area estimation [SAE] of people living with HIV [PLHIV], map of HIV-positive patients by residence, HIV risk-screening tool [HRST], and index testing [IT]) and four supportive strategies (alternative healthcare outlets, performance-based incentives for field testers, Project Extension for Community Healthcare Outcomes, and interactive dashboards). ECCP was deployed in nine of 10 states prioritized for ART scale-up. Weekly program data (October 2019-March 2020) were tracked and analyzed. RESULTS: Of the total 774 LGAs in Nigeria, using SAE, 103 (13.3%) high-burden LGAs were identified, in which 2605 (28.0%) out of 9,294 hotspots were prioritized by mapping newly identified PLHIV by residential addresses. Over 22 weeks, among 882,449 individuals screened using HRST, 723,993 (82.0%) were eligible and tested for HIV (state range, 43.7-90.4%), out of which 20,616 were positive. Through IT, an additional 3,724 PLHIV were identified. In total, 24,340 PLHIV were identified and 97.4% were linked to life-saving antiretroviral therapy. The number of newly identified PLHIV increased 17-fold over 22 weeks (week 1: 89; week 22: 1,632). Overall mean HIV positivity rate by state was 3.3% (range, 1.8-6.4%). CONCLUSION: Using ECCP in nine states in Nigeria increased the number of PLHIV in the community who knew their status, allowing them to access life-saving care and decreasing the risk of HIV transmission.

BACKGROUND: The need for accurate HIV annual program planning data motivated the compressed timeline for the 2018 Nigerian HIV/AIDS Indicator and Impact Survey (NAIIS). The survey team used stakeholder cooperation and responsive design, using survey process and paradata to refine survey implementation, to quickly collect high-quality data. We describe processes that led to generation of data for program and funding decisions, ensuring HIV services were funded in 2019. SETTING: Nigeria is the most populous country in Africa, with approximately 195 million people in 36 states and the Federal Capital Territory. Challenges include multiple security threats, poor infrastructure, seasonal rains, and varied health system capacity. METHODS: Stakeholders worked together to plan and implement NAIIS. Methods from other population-based HIV impact assessments were modified to meet challenges and the compressed timeline. Data collection was conducted in 6 webs. Responsive design included reviewing survey monitoring paradata and laboratory performance. Costs required to correct data errors, for example, staff time and transportation, were tracked. RESULTS: NAIIS data collection was completed in 23 weeks, ahead of the originally scheduled 24 weeks. Responsive design identified and resolved approximately 68,000 interview errors, affecting approximately 62,000 households, saving about US$4.4 million in costs. Biweekly field laboratory test quality control improved from 50% to 100% throughout NAIIS. CONCLUSIONS: Cooperation across stakeholders and responsive design ensured timely release of NAIIS results and informed planning for HIV epidemic control in Nigeria. Based on NAIIS results, funds were provided to place an additional 500,000 HIV-positive Nigerians on antiretroviral therapy by the end of 2020, pushing Nigeria toward epidemic control.

BACKGROUND: Machine learning has the potential to help researchers better understand and close the gap in HIV care delivery in large metropolitan regions such as Mecklenburg County, North Carolina, USA. OBJECTIVES: We aim to identify important risk factors associated with delayed linkage to care for HIV patients with novel machine learning models and identify high-risk regions of the delay. METHODS: Deidentified 2013-2017 Mecklenburg County surveillance data in eHARS format were requested. Both univariate analyses and machine learning random forest model (developed in R 3.5.0) were applied to quantify associations between delayed linkage to care (>30 days after diagnosis) and various risk factors for individual HIV patients. We also aggregated linkage to care by zip codes to identify high-risk communities within the county. RESULTS: Types of HIV-diagnosing facility significantly influenced time to linkage; first diagnosis in hospital was associated with the shortest time to linkage. HIV patients with lower CD4+ cell counts (<200/ml) were twice as likely to link to care within 30 days than those with higher CD4+ cell count. Random forest model achieved high accuracy (>80% without CD4+ cell count data and >95% with CD4+ cell count data) to predict risk of delay in linkage to care. In addition, we also identified top high-risk zip codes of delayed linkage. CONCLUSION: The findings helped public health teams identify high-risk communities of delayed HIV care continuum across Mecklenburg County. The methodology framework can be applied to other regions with HIV epidemic and challenge of delayed linkage to care.

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Alongside efforts to improve safe management of feces along the entire sanitation chain, including after the toilet, global sanitation efforts are focusing on universal access ‘basic’ services: onsite facilities that safely contain excreta away from human contact. Although fecal sludge management is improving in urban areas, open drains remain a common fate for feces in these often densely-populated neighborhoods in low-income countries. To-date, it is unclear to what extent complete coverage of onsite sanitation reduces fecal contamination in the urban environment and how fecal contamination varies within urban drains across neighborhoods by sanitation status within a city. We assessed how neighborhood levels of environmental fecal contamination (via spatially-representative sampling of open drains for E. coli) varied across four neighborhoods with varying income, type and coverage of household sanitation facilities, and population density in Accra, Ghana. Neighborhoods with very high sanitation coverage (≥89%) still had high (&gt;4 log10 CFU/100 mL) E. coli concentrations in drains. Between-neighborhood variation in E. coli levels among the high coverage neighborhoods was significant: drain concentrations in neighborhoods with 93% and 89% coverage (4.7 (95% CI: 4.5, 4.9) & 4.9 (95% CI: 4.5, 5.3) log10 CFU/100 mL, respectively) were higher than in the neighborhood with 97% coverage (4.1 log10 CFU/100 mL, 95% CI: 3.8, 4.4 log10 CFU/100 mL). Compared with the highest coverage neighborhood, the neighborhood with lowest coverage (48%) also had higher E. coli concentrations (5.6 log10 CFU/100 mL, 95% CI: 5.3, 5.9 log10 CFU/100 mL). Although fecal contamination in open drains appeared lower in neighborhoods with higher onsite sanitation coverage (and vice versa), other factors (e.g. fecal sludge management, animals, population density) may affect drain concentrations. These results underscore that neighborhood-level onsite sanitation improvements alone may not sufficiently reduce fecal hazards to public health from open drains. These findings supporting the need for integrated, city-level fecal sludge management alongside multifaceted interventions to reduce fecal contamination levels and human exposure.

Despite the availability of effective tetanus prevention strategies, as of 2016, Maternal and Neonatal Tetanus Elimination (MNTE) has not yet been achieved in 18 countries globally. In this paper, we review the status of MNTE in the World Health Organization African Region (AFR),and provide recommendations for achieving and maintaining MNTE in AFR. As of November 2016, 37 (79%) AFR countries have achieved MNTE, with 10 (21%) countries remaining. DTP3 coverage increased from 52% in 2000 to 76% in 2015. In 2015, coverage with at least 2 doses of tetanus containing vaccine (TT2+) and proportion of newborns protected at birth (PAB) were 69% and 77%, compared with 44% and 62% in 2000, respectively. Since 1999, over 79 million women of reproductive age (WRA) have been vaccinated with TT2+ through supplementary immunization activities (SIAs). Despite the progress, only 54% of births were attended by skilled birth attendants (SBAs), 5 (11%) countries provided the 3 WHO-recommended booster doses to both sexes, and about 5.5 million WRA still need to be reached with SIAs. Coverage disparities still exist between countries that have achieved MNTE and those that have not. In 2015, coverage with DTP3 and PAB were higher in MNTE countries compared with those yet to achieve MNTE: 84% vs. 68% and 86% vs. 69%, respectively. Challenges to achieving MNTE in the remaining AFR countries include weak health systems, competing priorities, insufficient funding, insecurity, and sub-optimal neonatal tetanus (NT) surveillance. To achieve and maintain MNTE in AFR, increasing SBAs and tetanus vaccination coverage, integrating tetanus vaccination with other opportunities (e.g., polio and measles campaigns, mother and child health days), and providing appropriately spaced booster doses are needed. Strengthening NT surveillance and conducting serosurveys would ensure appropriate targeting of MNTE activities and high-quality information for validating the achievement and maintenance of elimination.

BACKGROUND: Non-cold chain-dependent HIV rapid testing has been adopted in many resource-constrained nations as a strategy for reaching out to populations. HIV rapid test kits (RTKs) have the advantage of ease of use, low operational cost and short turnaround times. Before 2005, different RTKs had been used in Nigeria without formal evaluation. Between 2005 and 2007, a study was conducted to formally evaluate a number of RTKs and construct HIV testing algorithms. OBJECTIVES: The objectives of this study were to assess and select HIV RTKs and develop national testing algorithms. METHOD: Nine RTKs were evaluated using 528 well-characterised plasma samples. These comprised 198 HIV-positive specimens (37.5%) and 330 HIV-negative specimens (62.5%), collected nationally. Sensitivity and specificity were calculated with 95% confidence intervals for all nine RTKs singly and for serial and parallel combinations of six RTKs; and relative costs were estimated. RESULTS: Six of the nine RTKs met the selection criteria, including minimum sensitivity and specificity (both > 99.0%) requirements. There were no significant differences in sensitivities or specificities of RTKs in the serial and parallel algorithms, but the cost of RTKs in parallel algorithms was twice that in serial algorithms. Consequently, three serial algorithms, comprising four test kits (BundiTM, DetermineTM, Stat-Pak and Uni-GoldTM) with 100.0% sensitivity and 99.1% - 100.0% specificity, were recommended and adopted as national interim testing algorithms in 2007. CONCLUSION: This evaluation provides the first evidence for reliable combinations of RTKs for HIV testing in Nigeria. However, these RTKs need further evaluation in the field (Phase II) to re-validate their performance.