Under-five mortality before and after implementation of the Liberia National Community Health Assistant (NCHA) program: A study protocol.

Between 2018 and 2022 the Liberian Government implemented the National Community Health Assistant (NCHA) program to improve provision of maternal and child health care to underserved rural areas of the country. Whereas the contributions of this and similar community health worker (CHW) based healthcare programs have been associated with improved process measures, the impact of a governmental CHW program at scale on child mortality has not been fully established. We will conduct a cluster sampled, community-based survey with landmark event calendars to retrospectively assess child births and deaths among all children born to women in the Grand Bassa District of Liberia. We will use a mixed effects Cox proportional hazards model, taking advantage of the staggered program implementation in Grand Bassa districts over a period of 4 years to compare rates of under-5 child mortality between the pre- and post-NCHA program implementation periods. This study will be the first to estimate the impact of the Liberian NCHA program on under-5 mortality.

Identifying determinants of under-five child mortality in northern Togo.

Background: Although global rates of under-five mortality have declined, many low- and middle-income countries (LMICs), including Togo, have not achieved sufficient progress. We aimed to identify the structural and intermediary determinants associated with under-five mortality in northern Togo. Methods: We collected population-representative cross-sectional household surveys adapted from the Demographic Household Survey (DHS) and Multiple Indicator Cluster Survey from women of reproductive age in northern Togo in 2018. The primary outcome was under-five mortality for children born to respondents in the 10-year period prior to the survey. We selected structural and intermediary determinants of health from the World Health Organization Conceptual Framework for Action on the Social Determinants of Health. We estimated associations between determinants and under-five mortality for births in the last 10 years (model 1 and 2) and two years (model 3) using Cox proportional hazards models. Results: Of the 20 121 live births in the last 10 years, 982 (4.80%) children died prior to five years of age. Prior death of a sibling (adjusted hazard ratio (aHR) = 5.02; 95% confidence interval (CI) = 4.23-5.97), maternal ethnicity (i.e. Konkomba, Temberma, Lamba, Losso, or Peul), multiple birth status (aHR = 2.27; 95% CI = 1.78-2.90), maternal age under 25 years (women <19 years: aHR = 2.05; 95% CI = 1.75-2.39; women 20-24 years: aHR = 1.48; 95% CI = 1.29-1.68), lower birth interval (aHR = 1.51; 95% CI = 1.31-1.74), and higher birth order (second or third born: aHR = 1.45; 95% CI = 1.32-1.60; third or later born: aHR = 2.14; 95% CI = 1.74-2.63) were associated with higher hazard of under-five mortality. Female children had lower hazards of under-five mortality (aHR = 0.80; 95% CI = 0.73-0.89). Under-five mortality was also lower for children born in the last two years (n = 4852) whose mothers received any (aHR = 0.48; 95% CI = 0.30-0.78) or high quality (aHR = 0.51; 95% CI = 0.29-0.88) prenatal care. Conclusion: Compared to previous DHS estimates, under-five mortality has decreased in Togo, but remains higher than other LMICs. Prior death of a sibling and several intermediary determinants were associated with a higher risk of mortality, while receipt of prenatal care reduced that risk. These findings have significant implications on reducing disparities related to mortality through strengthening maternal and child health care delivery.

A repeated cross-sectional study of the association of community health worker intervention with the maternal continuum of care in rural Liberian communities.

BACKGROUND: The maternal continuum of care (CoC) (antenatal care, facility-based delivery, postnatal care) is critical to maternal and neonatal health and reducing mortality, but completion in rural areas of low- and middle-income countries is often limited. We used repeated cross-sectional household surveys from a rural Liberian county to explore changes in rates of completion of all steps and no steps in the maternal CoC after implementation of the National Community Health Assistant Program (NCHAP), a community health worker (CHW) intervention designed to increase care uptake for families over five kilometers from a facility. METHODS: We analyzed repeated cross-sectional household surveys of women aged 18-49 served by NCHAP in Rivercess County, Liberia. We measured survey-weighted, before-to-after implementation difference in completion of all steps and no steps in the maternal CoC. We used multivariable regression to explore covariates associated with completion rates before and after NCHAP implementation. RESULTS: Data from surveys conducted at three timepoints (2015, n = 354; 2018, n = 312; 2021, n = 302) were analyzed. A significant increase in completing the full maternal CoC (2015:23.6%, 2018:53.4%, change:29.7% points (pp), 95% confidence interval (CI) [21.0,38.4]) and a decrease in completing no steps in the CoC (2015:17.6%, 2018:4.0%, change: -12.4pp [-17.6, -7.2]) after implementation of NCHAP were observed from 2015 to 2018, with rates maintained from 2018 to 2021. Living farther from a facility was consistently associated with less care across the continuum. Following implementation, living in a motorbike accessible community was associated with completing the CoC while living in a mining community was negatively associated with omitting the CoC. Household wealth was associated with differences in rates pre-NCHAP but not post-NCHAP. CONCLUSIONS: Following NCHAP implementation, completion rate of the full maternal CoC in Rivercess County more than doubled while the rate of completing no steps in the continuum fell below 5%. These rates were sustained over time including during COVID-19 with reduced differences across wealth groups, although far distances remained a risk for less care. CHW programs providing active outreach to remote communities can be important tools for improving uptake of interventions and reducing risk of no formal care during and after pregnancy.

Does it matter that standard preparedness indices did not predict COVID-19 outcomes?

A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the need for a fundamental reassessment which better aligns preparedness measurement with operational capacities in real-world stress situations, including the points at which coordination structures and decision-making may fail. There are, however, several reasons why these instruments should not be so easily rejected as preparedness measures.From a methodological point of view, these studies use relatively simple outcome measures, mostly based on cumulative numbers of cases and deaths at a fixed point of time. A country's "success" in dealing with the pandemic is highly multidimensional - both in the health outcomes and type and timing of interventions and policies - is too complex to represent with a single number. In addition, the comparability of mortality data over time and among jurisdictions is questionable due to highly variable completeness and representativeness. Furthermore, the analyses use a cross-sectional design, which is poorly suited for evaluating the impact of interventions, especially for COVID-19.Conceptually, a major reason that current preparedness measures fail to predict pandemic outcomes is that they do not adequately capture variations in the presence of effective political leadership needed to activate and implement existing system, instill confidence in the government's response; or background levels of interpersonal trust and trust in government institutions and country ability needed to mount fast and adaptable responses. These factors are crucial; capacity alone is insufficient if that capacity is not effectively leveraged. However, preparedness metrics are intended to identify gaps that countries must fill. As important as effective political leadership and trust in institutions, countries cannot be held accountable to one another for having good political leadership or trust in institutions. Therefore, JEE scores, the GHSI, and similar metrics can be useful tools for identifying critical gaps in capacities and capabilities that are necessary but not sufficient for an effective pandemic response.

COVID-19 vaccine uptake, confidence and hesitancy in rural KwaZulu-Natal, South Africa between April 2021 and April 2022: A continuous cross-sectional surveillance study.

High COVID-19 vaccine hesitancy in South Africa limits protection against future epidemic waves. We evaluated how vaccine hesitancy and its correlates evolved April 2021-April 2022 in a well-characterized rural KwaZulu-Natal setting. All residents aged >15 in the Africa Health Research Institute's surveillance area were invited to complete a home-based, in-person interview. We described vaccine uptake and hesitancy trends, then evaluated associations with pre-existing personal factors, dynamic environmental context, and cues to action using ordinal logistic regression. Among 10,011 respondents, vaccine uptake rose as age-cohorts became vaccine-eligible before levelling off three months post-eligibility; younger age-groups had slower uptake and plateaued faster. Lifetime receipt of any COVID-19 vaccine rose from 3.0% in April-July 2021 to 32.9% in January-April 2022. Among 7,445 unvaccinated respondents, 47.7% said they would definitely take a free vaccine today in the first quarter of the study time period, falling to 32.0% in the last. By March/April 2022 only 48.0% of respondents were vaccinated or said they would definitely would take a vaccine. Predictors of lower vaccine hesitancy included being male (adjusted odds ratio [aOR]: 0.70, 95% confidence interval [CI]: 0.65-0.76), living with vaccinated household members (aOR:0.65, 95%CI: 0.59-0.71) and knowing someone who had had COVID-19 (aOR: 0.69, 95%CI: 0.59-0.80). Mistrust in government predicted greater hesitancy (aOR: 1.47, 95%CI: 1.42-1.53). Despite several COVID-19 waves, vaccine hesitancy was common in rural South Africa, rising over time and closely tied to mistrust in government. However, interpersonal experiences countered hesitancy and may be entry-points for interventions.

Behavioral Predictors of Intention to Use a Text Messaging Reminder System Among People Living With HIV in Rural Uganda: Survey Study.

BACKGROUND: The expansion of cellular phones in sub-Saharan Africa spurred the development of SMS text message-based mobile health (mHealth) technology. Numerous SMS text message-based interventions have attempted to increase retention in care for people living with HIV in sub-Saharan Africa. Many of these interventions have failed to scale. Understanding theory-grounded factors leading to mHealth acceptability is needed to create scalable, contextually appropriate, and user-focused interventions to improve longitudinal HIV care for people living with HIV in sub-Saharan Africa. OBJECTIVE: In this study, we aimed to understand the relationship between constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), constructs identified in previous qualitative research, and behavioral intention to use a novel SMS text message-based mHealth intervention designed to improve care retention among people living with HIV initiating treatment in rural Uganda. METHODS: We conducted a survey of people living with HIV who were newly initiating HIV care in Mbarara, Uganda, and had agreed to use a novel SMS text message-based system that notified them of abnormal laboratory results and reminded them to return to the clinic. Survey items assessed behavioral intention to use the SMS text messaging system; constructs from UTAUT; and demographics, literacy, SMS text messaging experience, HIV status disclosure, and social support. We used factor analysis and logistic regression to estimate the relationships between UTAUT constructs and the behavioral intention to use the SMS text messaging system. RESULTS: A total of 249 participants completed the surveys, of whom 115 (46.2%) expressed high behavioral intention to use the SMS text messaging intervention. In a multivariable analysis, we found that performance expectancy (adjusted odds ratio [aOR] of the scaled factor score 5.69, 95% CI 2.64-12.25; P<.001), effort expectancy (aOR of the scaled factor score 4.87, 95% CI 1.75-13.51; P=.002), and social influence (measured as a 1-unit Likert score increase in the perception that clinical staff have been helpful in the use of the SMS text messaging program; aOR 3.03, 95% CI 1.21-7.54; P=.02) were significantly associated with high behavioral intention to use the SMS text messaging program. SMS text messaging experience (aOR/1-unit increase 1.48, 95% CI 1.11-1.96; P=.008) and age (aOR/1-year increase 1.07, 95% CI 1.03-1.13; P=.003) were also significantly associated with increased odds of high intention to use the system. CONCLUSIONS: Performance expectancy, effort expectancy, and social influence, as well as age and SMS experience, were drivers of high behavioral intention to use an SMS text messaging reminder system among people living with HIV initiating treatment in rural Uganda. These findings highlight salient factors associated with SMS intervention acceptability in this population and indicate attributes that are likely to be key to the successful development and scaling of novel mHealth interventions.

How well do coverage surveys and programmatically reported mass drug administration coverage match? Results from 214 mass drug administration campaigns in 15 countries, 2008-2017.

INTRODUCTION: Delivering preventive chemotherapy through mass drug administration (MDA) is a central approach in controlling or eliminating several neglected tropical diseases (NTDs). Treatment coverage, a primary indicator of MDA performance, can be measured through routinely reported programmatic data or population-based coverage evaluation surveys. Reported coverage is often the easiest and least expensive way to estimate coverage; however, it is prone to inaccuracies due to errors in data compilation and imprecise denominators, and in some cases measures treatments offered as opposed to treatments swallowed. OBJECTIVE: Analyses presented here aimed to understand (1) how often coverage calculated using routinely reported data and survey data would lead programme managers to make the same programmatic decisions; (2) the magnitude and direction of the difference between these two estimates, and (3) whether there is meaningful variation by region, age group or country. METHODS: We analysed and compared reported and surveyed treatment coverage data from 214 MDAs implemented between 2008 and 2017 in 15 countries in Africa, Asia and the Caribbean. Routinely reported treatment coverage was compiled using data reported by national NTD programmes to donors, either directly or via NTD implementing partners, following the implementation of a district-level MDA campaign; coverage was calculated by dividing the number of individuals treated by a population value, which is typically based on national census projections and occasionally community registers. Surveyed treatment coverage came from post-MDA community-based coverage evaluation surveys, which were conducted as per standardised WHO recommended methodology. RESULTS: Coverage estimates using routine reporting and surveys gave the same result in terms of whether the minimum coverage threshold was reached in 72% of the MDAs surveyed in the Africa region and in 52% in the Asia region. The reported coverage value was within ±10 percentage points of the surveyed coverage value in 58/124 of the surveyed MDAs in the Africa region and 19/77 in the Asia region. Concordance between routinely reported and surveyed coverage estimates was 64% for the total population and 72% for school-age children. The study data showed variation across countries in the number of surveys conducted as well as the frequency with which there was concordance between the two coverage estimates. CONCLUSIONS: Programme managers must grapple with making decisions based on imperfect information, balancing needs for accuracy with cost and available capacity. The study shows that for many of the MDAs surveyed, based on the concordance with respect to reaching the minimum coverage thresholds, the routinely reported data were accurate enough to make programmatic decisions. Where coverage surveys do show a need to improve accuracy of routinely reported results, NTD programme managers should use various tools and approaches to strengthen data quality in order to use data for decision-making to achieve NTD control and elimination goals.

Measuring health system responsiveness in a national community health worker primary care programme in rural Liberia.

As many low- and middle-income countries scale up community health worker (CHW) programmes to achieve universal health coverage, ensuring quality as well as access is critical. Health system responsiveness (HSR) is a core domain of quality patient-centred care but has not been widely measured in CHW-delivered care. We report results from a household survey measuring HSR and health systems' quality of CHW-delivered care in two Liberian counties where the national CHW programme of Community Health Assistants (CHAs) for communities ≥5 km from a health centre has been implemented. We conducted a cross-sectional population-based household survey in 2019 in Rivercess (RC) and Grand Gedeh (GG) counties, using a two-stage cross-sectional cluster sampling approach. We included validated HSR questions on six responsiveness domains and patient-reported health system outcomes, such as satisfaction and trust in the CHA's skills and abilities. The HSR questions were administered to women aged 18-49 years who reported seeking care from a CHA in the 3 months prior to the survey. A composite responsiveness score was calculated and divided into tertiles. Multivariable analysis using Poisson regression with log link and adjusting for respondent characteristics was used to determine the association between responsiveness and patient-reported health system outcomes. The proportion of individuals rating responsiveness as very good or excellent was similar across all domains within a district, with ratings being lower in RC (23-29%) than in GG (52-59%). High ratings in both counties were seen for high trust in the CHA's skills and abilities (GG 84%, RC 75%) and high confidence in the CHA (GG 58%, RC 60%). Compared with women in the lowest responsiveness tertile (score ≤3), women in the highest tertile (score $ \ge $4.25) were significantly more likely to report high quality of CHA-delivered care (prevalence ratio, PR = 14.1), very good/excellent at meeting health needs (PR = 8.0), high confidence in the CHA to provide future care (PR = 2.4), and a high level of trust in CHA's skills and abilities (PR = 1.4). Controlling for respondent characteristics, the composite responsiveness score was significantly associated with all patient-reported health system outcomes (P < 0.001). We found that HSR was associated with important patient-reported health system quality outcomes, including satisfaction, trust, and confidence in the CHA. Measuring patients' experience and outcomes of care is important to complement more common measures of technical quality for CHW-delivered care to ensure that this domain of quality is central to the community health programme design and delivery.

The effect of interviewer-respondent age difference on the reporting of sexual activity in the Demographic and Health Surveys: Analysis of data from 21 countries.

Background: Interviewer effects can have consequential impacts on survey data, particularly for reporting sensitive attitudes and behaviours such as sexual activity and drug use, yet these effects remain understudied in low- and middle-income countries. The Demographic and Health Surveys (DHS) present a unique opportunity to study interviewer effects on the self-report of sensitive topics in low- and middle-income countries by including interviewer characteristics data. This paper aims to narrow the gap in research on interviewer effects by studying the effects that age difference between interviewer and respondent and interviewer survey experience have on the reporting of ever having sexual intercourse. Methods: We used DHS data from 91 066 women and 56 336 men in 21 countries where the standard DHS was implemented among all women of reproductive age, and interviewer characteristics were included in the data set. Using a Bayesian cross-classified model with random intercepts for interviewer and cluster, we assessed whether the effect of an age difference of 10 years or greater was associated with a difference in self-report of ever having sexual intercourse, adjusting for respondent demographics. Results: There was a meaningful association between an age difference of greater than ten years and reporting of ever having had sexual intercourse in most countries for both genders after adjusting for interviewer age and experience, rural or urban cluster, and individual-level characteristics. Among women, the marginal posterior probability of reporting ever having sexual intercourse if the interviewer was ten years or more years older was lower for 17 of 19 countries (countries ranged from -12.50 to 3.90 percentage points). Among men, the marginal posterior probability was lower for 16 of 20 countries, ranging from -18.30 to 17.10 percentage points. Conclusions: In most countries, women and men were less likely to report ever having sexual activity if the interviewer was ten or more years older than them, adjusting for potential confounders. These findings have important implications for interpreting numerous sexual health indicators, such as unmet family planning needs and human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) risk. Survey administrators may consider more careful interviewer-respondent characteristic matching or novel approaches like Audio Computer Assisted Self Interview to minimize interviewer-induced variance.

Validation of a Brief Internalized Sex-work Stigma Scale among Female Sex Workers in Kenya.

Female sex workers (FSW) often face severe stigma and discrimination and are extremely vulnerable to HIV and other sexually transmitted infections. In the fields of HIV and mental health, internalized stigma is associated with poor health care engagement. Due to the lack of valid, standardized measures for internalized sex work-related stigma, its dimensions and role are not well-understood. This study aimed to validate the six-item Internalized AIDS-Related Stigma Scale adapted to capture internalized sex work-related stigma by examining the scale's psychometric properties and performance among a cross-sectional, snowball sample of FSW (N = 497) in Kenya. While the original pre-hypothesized six-item model yielded acceptable CFI and SRMR values (CFI = 0.978 and SRMR = 0.038), the RMSEA was higher than desirable (RMSEA = 0.145). Our final four-item model demonstrated improved goodness of fit indices (RMSEA = 0.053; CFI = 0.999; and SRMR = 0.005). Both the pre-hypothesized six-item and reduced final four-item model demonstrated good internal consistency (Cronbach's alphas of 0.8162 and 0.8754, respectively). Higher levels of internalized stigma were associated with depression, riskier sexual behavior, and reduced condom use. This very brief measure will allow for reliable assessment of internalized stigma among FSW. Further investigation of internalized stigma among male sex workers, particularly the intersection of sex work-related and same-sex behavior-related stigmas, is needed.

Validating a measure of anticipated sex work-related stigma among male and female sex workers in Kenya.

Sex workers face different types of sex work-related stigma, which may include anticipated, perceived, experienced, or internalized stigma. Sex work stigma can discourage health care seeking and hamper STI and HIV prevention and treatment efforts. There is a paucity of validated sex work-related stigma measures, and this limits the ability to study the stigma associated with sex work. A cross-sectional survey was conducted that measured anticipated sex work-related stigma among male and female sex workers in Kenya (N = 729). We examined the construct validity and reliability of the anticipated stigma items to establish a conceptually and statistically valid scale. Our analysis supported a 15-item scale measuring five anticipated sex work stigma domains: gossip and verbal abuse from family; gossip and verbal abuse from healthcare workers; gossip and verbal abuse from friends and community; physical abuse; and exclusion. The scale demonstrated good face, content, and construct validity. Reliability was good for all subscales and the overall scale. The scale demonstrated good model fit statistics and good standardized factor loadings. The availability of valid and reliable stigma measures will enhance efforts to characterize and address stigma among sex workers and ultimately support the protection, health and well-being of this vulnerable population.

COVID-19 mortality in the United States: It's been two Americas from the start.

During the summer of 2021, a narrative of "two Americas" emerged: one with high demand for the COVID-19 vaccine and the second with widespread vaccine hesitancy and opposition to masks and vaccines. We analyzed "excess mortality" rates (the difference between total deaths and what would have been expected based on earlier time periods) prepared by the CDC for the United States from January 3, 2020 to September 26, 2021. Between Jan. 3, 2020 and Sept. 26, 2021, there were 895,693 excess deaths associated with COVID-19, 26% more than reported as such. The proportion of deaths estimated by the excess mortality method that was reported as COVID-19 was highest in the Northeast (92%) and lowest in the West (72%) and South (76%). Of the estimated deaths, 43% occurred between Oct. 4, 2020 and Feb. 27, 2021. Before May 31, 2020, approximately 56% of deaths were in the Northeast, where 17% of the population resides. Subsequently, 48% of deaths were in the South, which makes up 38% of the population. Since May 31, 2020, the South experienced COVID-19 mortality 26% higher than the national rate, whereas the Northeast's rate was 42% lower. If each region had the same mortality rate as the Northeast, more than 316,234 COVID-19 deaths between May 31, 2020 and Sept. 26, 2021 were "avoidable." More than half (63%) of the avoidable deaths occurred between May 31, 2020 and February, 2021, and more than half (60%) were in the South. Regional differences in COVID-19 mortality have been strong throughout the pandemic. The South has had higher mortality rates than the rest of the U.S. since May 31, 2020, and experienced 62% of the avoidable deaths. A comprehensive COVID-19 policy, including population-based restrictions as well as vaccines, is needed to control the pandemic.

COVID-19 data are messy: analytic methods for rigorous impact analyses with imperfect data.

BACKGROUND: The COVID-19 pandemic has led to an avalanche of scientific studies, drawing on many different types of data. However, studies addressing the effectiveness of government actions against COVID-19, especially non-pharmaceutical interventions, often exhibit data problems that threaten the validity of their results. This review is thus intended to help epidemiologists and other researchers identify a set of data issues that, in our view, must be addressed in order for their work to be credible. We further intend to help journal editors and peer reviewers when evaluating studies, to apprise policy-makers, journalists, and other research consumers about the strengths and weaknesses of published studies, and to inform the wider debate about the scientific quality of COVID-19 research. RESULTS: To this end, we describe common challenges in the collection, reporting, and use of epidemiologic, policy, and other data, including completeness and representativeness of outcomes data; their comparability over time and among jurisdictions; the adequacy of policy variables and data on intermediate outcomes such as mobility and mask use; and a mismatch between level of intervention and outcome variables. We urge researchers to think critically about potential problems with the COVID-19 data sources over the specific time periods and particular locations they have chosen to analyze, and to choose not only appropriate study designs but also to conduct appropriate checks and sensitivity analyses to investigate the impact(s) of potential threats on study findings. CONCLUSIONS: In an effort to encourage high quality research, we provide recommendations on how to address the issues we identify. Our first recommendation is for researchers to choose an appropriate design (and the data it requires). This review describes considerations and issues in order to identify the strongest analytical designs and demonstrates how interrupted time-series and comparative longitudinal studies can be particularly useful. Furthermore, we recommend that researchers conduct checks or sensitivity analyses of the results to data source and design choices, which we illustrate. Regardless of the approaches taken, researchers should be explicit about the kind of data problems or other biases that the design choice and sensitivity analyses are addressing.

Impact of the Liberian National Community Health Assistant Program on childhood illness care in Grand Bassa County, Liberia.

Liberia launched its National Community Health Assistant Program in 2016, which seeks to ensure that all people living 5 kilometers or farther from a health facility have access to trained, supplied, supervised, and paid community health workers (CHWs). This study aims to evaluate the impact of the national program following implementation in Grand Bassa County in 2018 using data from population-based surveys that included information on 1291 illness episodes. We measured before-to-after changes in care for childhood illness by qualified providers in a portion of the county that implemented in a first phase compared to those which had not yet implemented. We also assessed changes in whether children received oral rehydration therapy for diarrhea and malaria rapid diagnostic tests if they had a fever by a qualified provider (facility based or CHW). For these analyses, we used a difference-in-differences approach and adjusted for potential confounding using inverse probability of treatment weighting. We also assessed changes in the source from which care was received and examined changes by key dimensions of equity (distance from health facilities, maternal education, and household wealth). We found that care of childhood illness by a qualified provider increased by 60.3 percentage points (95%CI 44.7-76.0) more in intervention than comparison areas. Difference-in-differences for oral rehydration therapy and malaria rapid diagnostic tests were 37.6 (95%CI 19.5-55.8) and 38.5 (95%CI 19.9-57.0) percentage points, respectively. In intervention areas, care by a CHW increased from 0 to 81.6% and care from unqualified providers dropped. Increases in care by a qualified provider did not vary significantly by household wealth, remoteness, or maternal education. This evaluation found evidence that the Liberian National Community Health Assistant Program has increased access to effective care in rural Grand Bassa County. Improvements were approximately equal across three measured dimensions of marginalization.

Adjusting COVID-19 Seroprevalence Survey Results to Account for Test Sensitivity and Specificity.

Population-based seroprevalence surveys can provide useful estimates of the number of individuals previously infected with serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and still susceptible, as well as contribute to better estimates of the case-fatality rate and other measures of coronavirus disease 2019 (COVID-19) severity. No serological test is 100% accurate, however, and the standard correction that epidemiologists use to adjust estimates relies on estimates of the test sensitivity and specificity often based on small validation studies. We have developed a fully Bayesian approach to adjust observed prevalence estimates for sensitivity and specificity. Application to a seroprevalence survey conducted in New York State in 2020 demonstrates that this approach results in more realistic-and narrower-credible intervals than the standard sensitivity analysis using confidence interval endpoints. In addition, the model permits incorporating data on the geographical distribution of reported case counts to create informative priors on the cumulative incidence to produce estimates and credible intervals for smaller geographic areas than often can be precisely estimated with seroprevalence surveys.

Financial Assistance for Health Security: Effects of International Financial Assistance on Capacities for Preventing, Detecting, and Responding to Public Health Emergencies.

BACKGROUND: Health security funding is intended to improve capacities for preventing, detecting, and responding to public health emergencies. Recent years have witnessed substantial increases in the amounts of donor financial assistance to health security from countries, philanthropies, and other development partners. To date, no work has examined the effects of assistance on health security capacity development over time. This paper presents an analysis of the time-lagged effects of assistance for health security (AHS) on levels of capacity. METHODS: We collected publicly available health security assessment scores published between 2010 and 2019 and data relating to financial AHS. Using validated methods, we rescaled assessment scores on analogous scales to enable comparison and binned them in quartiles. We then used a distributed lag model (DLM) in a Bayesian ordinal regression framework to assess the effects of AHS on capacity development over time. RESULTS: Strong evidence exists for associations between financial assistance and select capacities on a variety of lagged time intervals. Financial assistance had positive effects on zoonotic disease capacities in the year it was disbursed, and positive effects on legislation, laboratory, workforce, and risk communication capacities one year after disbursal. Financial assistance had negative effects on laboratory and emergency response capacities two years after it was disbursed. Financial assistance did not have measurable effects on coordination, antimicrobial resistance (AMR), food safety, biosafety, surveillance, or response preparedness capacities over the timeframe considered. CONCLUSION: Financial AHS is associated with positive effects for several core health security capacities. However, for the majority of capacities, levels of funding were not significantly associated with capacity level, though we cannot fully exclude endogeneity. Future work should continue to investigate these relationships in different contexts and examine other factors that may contribute to capacity development.

Measuring Knowledge of Community Health Workers at the Last Mile in Liberia: Feasibility and Results of Clinical Vignette Assessments.

INTRODUCTION: Community health workers (CHWs) can provide lifesaving treatment for children in remote areas, but high-quality care is essential for effective delivery. Measuring the quality of community-based care in remote areas is logistically challenging. Clinical vignettes have been validated in facility settings as a proxy for competency. We assessed feasibility and effectiveness of clinical vignettes to measure CHW knowledge of integrated community case management (iCCM) in Liberia's national CHW program. METHODS: We developed 3 vignettes to measure knowledge of iCCM illnesses (malaria, diarrhea, and pneumonia) in 4 main areas: assessment, diagnosis, treatment, and caregiver instructions. Trained nurse supervisors administered the vignettes to CHWs in 3 counties in rural Liberia as part of routine program supervision between January and May 2019, collected data on CHW knowledge using a standardized checklist tool, and provided feedback and coaching to CHWs in real time after vignette administration. Proportions of vignettes correctly managed, including illness classification, treatment, and referral where necessary, were calculated. We assessed feasibility, defined as the ability of clinical supervisors to administer the vignettes integrated into their routine activities once per year for each CHW, and effectiveness, defined as the ability of the vignettes to measure the primary outcomes of CHW knowledge of diagnosis and treatment including referrals. RESULTS: We were able to integrate this assessment into routine supervision, facilitate real-time coaching, and collect data on iCCM knowledge among 155 CHWs through delivery of 465 vignettes. Diagnosis including severity was correct in 65%-82% of vignettes. CHWs correctly identified danger signs in 44%-50% of vignettes, correctly proposed referral to the facility in 63% of vignettes including danger signs, and chose correct lifesaving treatment in 23%-65% of vignettes. Both diagnosis and lifesaving treatment rates were highest for malaria and lowest for severe pneumonia. CONCLUSION: Administration of vignettes to assess knowledge of correct iCCM case management was feasible and effective in producing results in this setting. Proportions of correct diagnosis and lifesaving treatment varied, with high proportions for uncomplicated disease, but lower for more severe cases, with accurate recognition of danger signs posing a challenge. Future work includes validation of vignettes for use with CHWs through direct observation, strengthening supportive supervision, and program interventions to address identified knowledge gaps.

Interpreting COVID-19 Test Results in Clinical Settings: It Depends!

Tests for Coronavirus disease 2019 (COVID-19) are intended for a disparate and shifting range of purposes: (1) diagnosing patients who present with symptoms to inform individual treatment decisions; (2) organizational uses such as "cohorting" potentially infected patients and staff to protect others; and (3) contact tracing, surveillance, and other public health purposes. Often lost when testing is encouraged is that testing does not by itself confer health benefits. Rather, testing is useful to the extent it forms a critical link to subsequent medical or public health interventions. Such interventions might be individual level, like better diagnosis, treatment, isolation, or quarantine of contacts. They might aid surveillance to understand levels and trends of disease within a defined population that enables informed decisions to implement or relax social distancing measures. In this article, we describe the range of available COVID-19 tests; their accuracy and timing considerations; and the specific clinical, organizational, and public health considerations that warrant different testing strategies. Three representative clinical scenarios illustrate the importance of appropriate test use and interpretation. The reason a patient seeks testing is often a strong indicator of the pretest probability of infection, and thus how to interpret test results. In addition, the level of population spread of the virus and the timing of testing play critical roles in the positive or negative predictive value of the test. We conclude with practical recommendations regarding the need for testing in various contexts, appropriate tests and testing methods, and the interpretation of test results.

Complex relationship between household wealth, location of residence, road crash injury incidence and injury severity in Uganda.

BACKGROUND: Limited evidence exists about associations between road crash injury and economic status in sub-Saharan Africa from large, population-based data sets. Existing studies generally do not incorporate fatal crashes. This study aims to understand the relationship between relative wealth and road crash injury and severity using population-representative cross-sectional data from Uganda's 2016 Demographic and Health Survey . METHODS: One-year road crash risk was flexibly modelled as a function of wealth using fractional polynomial models, stratified by sex and rural/urban residence. Wealth was operationalised as 1/20th quantiles of the first principal component from a polychoric principal component analysis. Injury severity was coded as a three-level ordinal variable; associations with wealth were modelled with ordinal logistic regression on quintiles of relative wealth, stratified by residence. RESULTS: Overall, injury risk peaked in the upper middle of the wealth distribution. Rural resident injury risk increased monotonically with wealth. Urban resident risk had an upside-down U shape. Risk peaked in the distribution's middle at about double the lowest levels. Only urban men had higher risk among the least wealthy than most wealthy (3.2% vs 1.7%; difference=1.5 percentage points, 95% CI 0.2 to 2.7). Among those with road crash injuries, greater relative wealth was associated with decreased likelihood of more severe injury (33.2 percentage points lower in the highest category than lowest, 95% CI 18.4 to 48.1) or death (5.9 percentage points, 95% CI -0.1 to 11.8) for urban residents but not rural residents. CONCLUSION: Relationships between relative wealth and injury risk and severity are complex and different for urban and rural Ugandans.

Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study.

BACKGROUND: Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. OBJECTIVE: We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. METHODS: We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. RESULTS: We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. CONCLUSIONS: Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.