Severe Acute Respiratory Syndrome Coronavirus 2 Neutralizing Antibody Responses After Community Infections in Children and Adults.

Background: We compared postinfection severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibody (nAb) responses among children and adults while the D614G-like strain and Alpha, Iota, and Delta variants circulated. Methods: During August 2020-October 2021, households with adults and children were enrolled and followed in Utah, New York City, and Maryland. Participants collected weekly respiratory swabs that were tested for SARS-CoV-2 and had sera collected during enrollment and follow-up. Sera were tested for SARS-CoV-2 nAb by pseudovirus assay. Postinfection titers were characterized with biexponential decay models. Results: Eighty participants had SARS-CoV-2 infection during the study (47 with D614G-like virus, 17 with B.1.1.7, and 8 each with B.1.617.2 and B.1.526 virus). Homologous nAb geometric mean titers (GMTs) trended higher in adults (GMT = 2320) versus children 0-4 (GMT = 425, P = .33) and 5-17 years (GMT = 396, P = .31) at 1-5 weeks postinfection but were similar from 6 weeks. Timing of peak titers was similar by age. Results were consistent when participants with self-reported infection before enrollment were included (n = 178). Conclusions: The SARS-CoV-2 nAb titers differed in children compared to adults early after infection but were similar by 6 weeks postinfection. If postvaccination nAb kinetics have similar trends, vaccine immunobridging studies may need to compare nAb responses in adults and children 6 weeks or more after vaccination.

Patient and Epidemiological Factors Associated With Influenza Testing in Hospitalized Adults With Acute Respiratory Illnesses, 2016-2017 to 2019-2020.

Background: Data are limited on influenza testing among adults with acute respiratory illness (ARI)-associated hospitalizations. We identified factors associated with influenza testing in adult ARI-associated hospitalizations across the 2016-2017 through 2019-2020 influenza seasons. Methods: Using data from 4 health systems in the United States, we identified hospitalizations that had an ARI discharge diagnosis or respiratory virus test. A hospitalization with influenza testing was based on testing performed within 14 days before through 72 hours after admission. We used random forest analysis to identify patient characteristics and influenza activity indicators that were most important in terms of their relationship to influenza testing. Results: Across 4 seasons, testing rates ranged from 14.8%-19.4% at 3 pooled sites and 60.1%-78.5% at a fourth site with different testing practices. Discharge diagnoses of pneumonia or infectious disease of noninfluenza etiology, presence of ARI signs/symptoms, hospital admission month, and influenza-like illness activity level were consistently among the variables with the greatest relative importance. Conclusions: Select ARI diagnoses and indicators of influenza activity were the most important factors associated with influenza testing among ARI-associated hospitalizations. Improved understanding of which patients are tested may enhance influenza burden estimates and allow for more timely clinical management of influenza-associated hospitalizations.

Epidemiology and risk factors related to severity of clinical manifestations of COVID-19 in outpatients: A retrospective study in Haiti.

BACKGROUND: Haiti's first COVID-19 cases were confirmed on March 18, 2020, and subsequently spread throughout the country. The objective of this study was to describe clinical manifestations of COVID-19 in Haitian outpatients and to identify risk factors for severity of clinical manifestations. METHODS: We conducted a retrospective study of COVID-19 outpatients diagnosed from March 18-August 4, 2020, using demographic, epidemiological, and clinical data reported to the Ministry of Health (MoH). We used univariate and multivariate analysis, including multivariable logistic regression, to explore the risk factors and specific symptoms related to persons with symptomatic COVID-19 and the severity of symptomatic COVID-19 disease. RESULTS: Of 5,389 cases reported to MOH during the study period, 1,754 (32.5%) were asymptomatic. Amongst symptomatic persons 2,747 (75.6%) had mild COVID-19 and 888 (24.4%) had moderate-to-severe disease; the most common symptoms were fever (69.6%), cough (51.9%), and myalgia (45.8%). The odds of having moderate-to-severe disease were highest among persons with hypertension (aOR = 1.72, 95% Confidence Interval [CI] (1.34, 2.20), chronic pulmonary disease (aOR = 3.93, 95% CI (1.93, 8.17)) and tuberculosis (aOR = 3.44, 95% CI (1.35, 9.14)) compared to persons without those conditions. The odds of having moderate-to-severe disease increased with age but was also seen among children aged 0-4 years (OR: 1.73, 95% CI (0.93, 3.08)), when using 30-39 years old as the reference group. All of the older age groups, 50-64 years, 65-74 years, 75-84 years, and 85+ years, had significantly higher odds of having moderate-to-severe COVID-19 compared with ages 30-39 years. Diabetes was associated with elevated odds of moderate-to-severe disease in bivariate analysis (OR = 2.17, 95% CI (1.58,2.98) but, this association did not hold in multivariable analyses (aOR = 1.22,95%CI (0.86,1.72)). CONCLUSION: These findings from a resource-constrained country highlight the importance of surveillance systems to track emerging infections and their risk factors. In addition to co-morbidities described elsewhere, tuberculosis was a risk factor for moderate-to-severe COVID-19 disease.

Estimated Number of COVID-19 Infections, Hospitalizations, and Deaths Prevented Among Vaccinated Persons in the US, December 2020 to September 2021.

Importance: The number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated persons, independent of the effect of reduced transmission, is a key measure of vaccine impact. Objective: To estimate the number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated adults in the US. Design, Setting, and Participants: In this modeling study, a multiplier model was used to extrapolate the number of SARS-CoV-2 infections and COVID-19-associated deaths from data on the number of COVID-19-associated hospitalizations stratified by state, month, and age group (18-49, 50-64, and ≥65 years) in the US from December 1, 2020, to September 30, 2021. These estimates were combined with data on vaccine coverage and effectiveness to estimate the risks of infections, hospitalizations, and deaths. Risks were applied to the US population 18 years or older to estimate the expected burden in that population without vaccination. The estimated burden in the US population 18 years or older given observed levels of vaccination was subtracted from the expected burden in the US population 18 years or older without vaccination (ie, counterfactual) to estimate the impact of vaccination among vaccinated persons. Exposures: Completion of the COVID-19 vaccination course, defined as 2 doses of messenger RNA (BNT162b2 or mRNA-1273) vaccines or 1 dose of JNJ-78436735 vaccine. Main Outcomes and Measures: Monthly numbers and percentages of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented were estimated among those who have been vaccinated in the US. Results: COVID-19 vaccination was estimated to prevent approximately 27 million (95% uncertainty interval [UI], 22 million to 34 million) infections, 1.6 million (95% UI, 1.4 million to 1.8 million) hospitalizations, and 235 000 (95% UI, 175 000-305 000) deaths in the US from December 1, 2020, to September 30, 2021, among vaccinated adults 18 years or older. From September 1 to September 30, 2021, vaccination was estimated to prevent 52% (95% UI, 45%-62%) of expected infections, 56% (95% UI, 52%-62%) of expected hospitalizations, and 58% (95% UI, 53%-63%) of expected deaths in adults 18 years or older. Conclusions and Relevance: These findings indicate that the US COVID-19 vaccination program prevented a substantial burden of morbidity and mortality through direct protection of vaccinated individuals.

Estimating COVID-19 Hospitalizations in the United States With Surveillance Data Using a Bayesian Hierarchical Model: Modeling Study.

BACKGROUND: In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important. OBJECTIVE: We aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19. METHODS: We estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data. RESULTS: We estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states. CONCLUSIONS: Our novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.

Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Reported Coronavirus Disease 2019 Cases in US Children, August 2020-May 2021.

BACKGROUND: Case-based surveillance of pediatric coronavirus disease 2019 (COVID-19) cases underestimates the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children and adolescents. Our objectives were to estimate monthly SARS-CoV-2 antibody seroprevalence and calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 8 US states. METHODS: Using data from the Nationwide Commercial Laboratory Seroprevalence Survey, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0-17 years from August 2020 through May 2021. We calculated and compared cumulative incidence of SARS-CoV-2 infection extrapolated from population-standardized seroprevalence of antibodies to SARS-CoV-2, cumulative COVID-19 case reports since March 2020, and infection-to-case ratios among persons of all ages and children aged 0-17 years for each state. RESULTS: Of 41 583 residual serum specimens tested, children aged 0-4, 5-11, and 12-17 years accounted for 1619 (3.9%), 10 507 (25.3%), and 29 457 (70.8%), respectively. Median SARS-CoV-2 antibody seroprevalence among children increased from 8% (range, 6%-20%) in August 2020 to 37% (range, 26%-44%) in May 2021. Estimated ratios of SARS-CoV-2 infections to reported COVID-19 cases in May 2021 ranged by state from 4.7-8.9 among children and adolescents to 2.2-3.9 for all ages combined. CONCLUSIONS: Through May 2021 in selected states, the majority of children with serum specimens included in serosurveys did not have evidence of prior SARS-CoV-2 infection. Case-based surveillance underestimated the number of children infected with SARS-CoV-2 more than among all ages. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies.

Coronavirus Disease Case Definitions, Diagnostic Testing Criteria, and Surveillance in 25 Countries with Highest Reported Case Counts.

We compared case definitions for suspected, probable, and confirmed coronavirus disease (COVID-19), as well as diagnostic testing criteria, used in the 25 countries with the highest reported case counts as of October 1, 2020. Of the identified countries, 56% followed World Health Organization (WHO) recommendations for using a combination of clinical and epidemiologic criteria as part of the suspected case definition. A total of 75% of identified countries followed WHO recommendations on using clinical, epidemiologic, and diagnostic criteria for probable cases; 72% followed WHO recommendations to use PCR testing to confirm COVID-19. Finally, 64% of countries used testing eligibility criteria at least as permissive as WHO. We observed marked heterogeneity in testing eligibility requirements and in how countries define a COVID-19 case. This heterogeneity affects the ability to compare case counts, transmission, and vaccine effectiveness, as well as estimates derived from case surveillance data across countries.

Global Health Security Preparedness and Response: An Analysis of the Relationship between Joint External Evaluation Scores and COVID-19 Response Performance.

OBJECTIVES: The COVID-19 pandemic has highlighted the importance and complexity of a country's ability to effectively respond. The Joint External Evaluation (JEE) assessment was launched in 2016 to assess a country's ability to prevent, detect and respond to public health emergencies. We examined whether JEE indicators could be used to predict a country's COVID-19 response performance to tailor a country's support more effectively. DESIGN: From April to August 2020, we conducted interviews with Centers for Disease Control and Prevention country offices that requested COVID-19 support and previously completed the JEE (version 1.0). We used an assessment tool, the 'Emergency Response Capacity Tool' (ERCT), to assess COVID-19 response performance. We analysed 28 ERCT indicators aligned with eight JEE indicators to assess concordance and discordance using strict agreement and weighted kappa statistics. Generalised estimating equation (GEE) models were used to generate predicted probabilities for ERCT scores using JEE scores as the independent model variable. RESULTS: Twenty-three countries met inclusion criteria. Of the 163 indicators analysed, 42.3% of JEE and ERCT scores were in agreement (p value=0.02). The JEE indicator with the highest agreement (62%) was 'Emergency Operations Center (EOC) operating procedures and plans', while the lowest (16%) was 'capacity to activate emergency operations'. Findings were consistent with weighted kappa statistics. In the GEE model, EOC operating procedures and plans had the highest predicted probability (0.86), while indicators concerning response strategy and coordination had the lowest (≤0.5). CONCLUSIONS: Overall, there was low agreement between JEE scores and COVID-19 response performance, with JEE scores often trending higher. JEE indicators concerning coordination and operations were least predictive of COVID-19 response performance, underscoring the importance of not inferring country response readiness from JEE scores alone. More in-depth country-specific investigations are likely needed to accurately estimate response capacity and tailor countries' global health security activities.

"No weight for height" case detection strategies for therapeutic feeding programs: sensitivity to acute malnutrition and target composition based on representative surveys in humanitarian settings.

BACKGROUND: One newly proposed approach to determining eligibility of children aged 6-59 months for therapeutic feeding programs (TFPs) is to use mid-upper arm circumference (MUAC) < 115 mm, bilateral oedema or Weight-for-Age Z-score (WAZ) < - 3 as admission criteria (MUAC+SWAZ). We explored potential consequences of this approach on the eligibility for treatment, as compared with the existing WHO normative guidance. We also compared sensitivity and specificity parameters of this approach for detecting wasted children to the previously described "Expanded MUAC" approach. METHODS: We analyzed data from 558 population representative cross-sectional cluster surveys conducted since 2007. We retrieved all children classified as severe acute malnutrition (SAM), moderate acute malnutrition (MAM), and those who are both wasted and stunted (WA + ST), and calculated proportions of previously eligible children who would now be excluded from treatment, as well as proportions of non-malnourished children among those who would become eligible. We also analyzed the expected changes in the number and demographics (sex, age) of the selected populations of children according to the different admission approaches. RESULTS: Both MUAC+SWAZ and Expanded MUAC case detection approaches substantially increase the sensitivity in detecting SAM, as compared to an approach which restricts detection of SAM cases to MUAC< 115 mm and oedema. Improved sensitivity however is attained at the expense of specificity and would require a very large increase of the size of TFPs, while still missing a non-negligible proportion (20-25%) of the SAM caseload. While our results confirm the sensitivity of the MUAC+SWAZ case detection approach in detecting WA + ST (over 80%), they show, on the other hand, that about half of the additional target detected by using SWAZ criterion will be neither SAM nor WA + ST. CONCLUSIONS: These results suggest that recently promoted approaches to case detection inflate TFPs' targets through the allocation of treatment to large numbers of children who have not been shown to require this type of support, including a significant proportion of non-acutely malnourished children in the MUAC+SWAZ approach. Considering the scarcity of resources for the implementation of TFPs, the rationale of abandoning the use of WHZ and of these alternative case detection strategies need to be critically reviewed.

Comparison of anthropometric data quality in children aged 6-23 and 24-59 months: lessons from population-representative surveys from humanitarian settings.

BACKGROUND: Ensuring the quality of anthropometry data is paramount for getting accurate estimates of malnutrition prevalence among children aged 6-59 months in humanitarian and refugee settings. Previous reports based on data from Demographic and Health Surveys suggested systematic differences in anthropometric data quality between the younger and older groups of preschool children. METHODS: We analyzed 712 anthropometric population-representative field surveys from humanitarian and refugee settings conducted during 2011-2018. We examined and compared the quality of five anthropometric indicators in children aged 6-23 months and children aged 24-59 months: weight for height, weight for age, height for age, body mass index for age and mid-upper arm circumference (MUAC) for age. Using the z-score distribution of each indicator, we calculated the following parameters: standard deviation (SD), percentage of outliers, and measures of distribution normality. We also examined and compared the quality of height, weight, MUAC and age measurements using missing data and rounding criteria. RESULTS: Both SD and percentage of flags were significantly smaller on average in older than in younger age group for all five anthropometric indicators. Differences in SD between age groups did not change meaningfully depending on overall survey quality or on the quality of age ascertainment. Over 50% of surveys overall did not deviate significantly from normality. The percentage of non-normal surveys was higher in older than in the younger age groups. Digit preference score for weight, height and MUAC was slightly higher in younger age group, and for age slightly higher in the older age group. Children with reported exact date of birth (DOB) had much lower digit preference for age than those without exact DOB. SD, percentage flags and digit preference scores were positively correlated between the two age groups at the survey level, such as those surveys showing higher anthropometry data quality in younger age group also tended to show higher quality in older age group. CONCLUSIONS: There should be an emphasis on increased rigor of training survey measurers in taking anthropometric measurements in the youngest children. Standardization test, a mandatory component of the pre-survey measurer training and evaluation, of 10 children should include at least 4-5 children below 2 years of age.

Effectiveness of clinical training on improving essential newborn care practices in Bossaso, Somalia: a pre and postintervention study.

BACKGROUND: Increasingly, neonatal mortality is concentrated in settings of conflict and political instability. To promote evidence-based practices, an interagency collaboration developed the Newborn Health in Humanitarian Settings: Field Guide. The essential newborn care component of the Field Guide was operationalized with the use of an intervention package encompassing the training of health workers, newborn kit provisions and the installation of a newborn register. METHODS: We conducted a quasi-experimental prepost study to test the effectiveness of the intervention package on the composite outcome of essential newborn care from August 2016 to December 2018 in Bossaso, Somalia. Data from the observation of essential newborn care practices, evaluation of providers' knowledge and skills, postnatal interviews, and qualitative information were analyzed. Differences in two-proportion z-tests were used to estimate change in essential newborn care practices. A generalized estimating equation was applied to account for clustering of practice at the health facility level. RESULTS: Among the 690 pregnant women in labor who sought care at the health facilities, 89.9% (n = 620) were eligible for inclusion, 84.7% (n = 525) were enrolled, and newborn outcomes were ascertained in 79.8% (n = 419). Providers' knowledge improved from pre to posttraining, with a mean difference in score of + 11.9% (95% CI: 7.2, 16.6, p-value < 0.001) and from posttraining to 18-months after training with a mean difference of + 10.9% (95% CI: 4.7, 17.0, p-value < 0.001). The proportion of newborns who received two or more essential newborn care practices (skin-to-skin contact, early breastfeeding, and dry cord care) improved from 19.9% (95% CI: 4.9, 39.7) to 94.7% (95% CI: 87.7, 100.0). In the adjusted model that accounted for clustering at health facilities, the odds of receiving two or more essential newborn practices was 64.5 (95% CI: 15.8, 262.6, p-value < 0.001) postintervention compared to preintervention. Predischarge education offered to mothers on breastfeeding 16.5% (95% CI: 11.8, 21.1) vs 44.2% (95% CI: 38.2, 50.3) and newborn illness danger signs 9.1% (95% CI: 5.4, 12.7) vs 5.0% (95% CI: 2.4, 7.7) remained suboptimal. CONCLUSIONS: The intervention package was feasible and effective in improving essential newborn care. Knowledge and skills gained after training were mostly retained at the 18-month follow-up.

Noncommunicable disease burden among conflict-affected adults in Ukraine: A cross-sectional study of prevalence, risk factors, and effect of conflict on severity of disease and access to care.

BACKGROUND: There is limited research on noncommunicable diseases (NCDs) in humanitarian settings despite the overall global burden and disproportionate growth in many conflicts and disaster-prone settings. This study aimed to determine the prevalence of NCDs and assess the perceived effect of conflict on NCD severity and access to treatment among conflict-affected adults (≥ 30 years) in Ukraine. METHODS AND FINDINGS: We conducted two population-representative, stratified, cross-sectional household surveys: one among adult internally displaced people (IDPs) throughout Ukraine and one among adults living in Donbas in eastern Ukraine. One randomly selected adult per household answered questions about their demographics, height and weight, diagnosed NCDs, access to medications and healthcare since the conflict began, as well as questions assessing psychological distress, trauma exposure, and posttraumatic stress disorder. More than half of participants reported having at least one NCD (55.7% Donbas; 59.8% IDPs) A higher proportion of IDPs compared to adults in Donbas experienced serious psychological distress (29.9% vs. 18.7%), interruptions in care (9.7-14.3% vs. 23.1-51.3%), and interruptions in medication than adults in Donbas (14.9-45.6% vs. 30.2-77.5%). Factors associated with perceived worsening of disease included psychological distress (p: 0.002-0.043), displacement status (IDP vs. Donbas) (p: <0.001-0.011), interruptions in medication (p: 0.002-0.004), and inability to see a doctor at some point since the start of the conflict (p: <0.001-0.008). CONCLUSIONS: Our study found a high burden of NCDs among two conflict-affected populations in Ukraine and identified obstacles to accessing care and medication. Psychological distress, interruptions to care, and interruptions in medication were all reported by a higher proportion of IDPs than adults in Donbas. There is a need for targeted policies and programs to support the unique needs of displaced conflict-affected individuals in Ukraine that address the economic and perceived barriers to NCD treatment and care.

Potential consequences of expanded MUAC-only programs on targeting of acutely malnourished children and ready-to-use-therapeutic-food allocation: lessons from cross-sectional surveys.

BACKGROUND: Some of the recently piloted innovative approaches for the management of acute malnutrition in children use the "expanded MUAC-only" approach, with Mid Upper Arm Circumference (MUAC) < 125 mm as the sole anthropometric criterion for screening and admission, classification of cases as severe using the 115 mm cut-off, and use Ready-to-Use-Therapeutic-Food (RUTF) for the management of both moderate (MAM) and severe (SAM) cases of acute malnutrition. Our study aimed at exploring the potential consequences of this "expanded MUAC-only" program scenario on the eligibility for treatment and RUTF allocation, as compared with the existing WHO normative guidance. METHODS: We analyzed data from 550 population representative cross-sectional cluster surveys conducted since 2007. We retrieved all children classified as SAM and MAM according to currently used case definitions, and calculated the proportions of SAM children who would be excluded from treatment, misclassified as MAM, or whose specific risks (because of having both MUAC and weight-for height deficits) would be ignored. We also analyzed the expected changes in the number and demographics (sex, age) of children meant to receive RUTF according to the new approach. RESULTS: We found that approximately one quarter of SAM children would not be detected and eligible for treatment under the "expanded MUAC-only" scenario, and another 20% would be classified as MAM. A further 17% of the total SAM children would be admitted and followed only according to their MUAC or oedema status, while they also present with a severe weight-for height deficit on admission. Considering MAM targeting, about half of the MAM children would be left undetected. This scenario also shows a 2.5 time increase in the number of children targeted with RUTF, with approximately 70% of MAM and 30% of SAM cases among this new RUTF target. CONCLUSIONS: This empirical evidence suggests that adoption of "expanded MUAC-only" programs would likely lead to a priori exclusion from treatment or misclassifying as MAM a large proportion of SAM cases, while redirecting programmatic costs in favor of those less in need. It underscores the need to explore other options for improving the impact of programs addressing the needs of acutely malnourished children.

Essential newborn care practice at four primary health facilities in conflict affected areas of Bossaso, Somalia: a cross-sectional study.

BACKGROUND: Newborn mortality is increasingly concentrated in contexts of conflict and political instability. However, there are limited guidelines and data on the availability and quality of newborn care in conflict settings. In 2016, an interagency collaboration developed the Newborn Health in Humanitarian Settings Field Guide- Interim version (Field Guide). In this study, we sought to understand the baseline availability and quality of essential newborn care in Bossaso, Somalia as part of an investigation to determine the feasibility and effectiveness of the Field Guide in improving newborn care in humanitarian settings. METHODS: A cross-sectional study was conducted at four purposely selected health facilities serving internally displaced persons affected by conflict in Bossaso. Essential newborn care practice and patient experience with childbirth care received at the facilities were assessed via observation of clinical practice during childbirth and the immediate postnatal period, and through postnatal interviews of mothers. Descriptive statistics and logistic regression were employed to summarize and examine variation by health facility. RESULTS: Of the 332 pregnant women approached, 253 (76.2%) consented and were enrolled. 97.2% (95% CI: 94.4, 98.9) had livebirths and 2.8% (95% CI: 1.1, 5.6) had stillbirths. The early newborn mortality was 1.7% (95% CI: 0.3, 4.8). Nearly all [95.7%, (95% CI: 92.4, 97.8)] births were attended by skilled health worker. Similarly, 98.0% (95% CI: 95.3, 99.3) of newborns received immediate drying, and 99.2% (95% CI: 97.1, 99.9) had delayed bathing. Few [8.6%, (95% CI: 5.4, 12.9)] received immediate skin-to-skin contact and the practice varied significantly by facility (p < 0.001). One-third of newborns [30.1%, (95% CI: 24.4, 36.2)] received early initiation of breastfeeding and there was significant variation by facility (p < 0.001). While almost all [99.2%, (95% CI: 97.2, 100)] service providers wore gloves while attending births, handwashing was not as common [20.2%, (95% CI: 15.4, 25.6)] and varied by facility (p < 0.001). Nearly all [92%, (95% CI: 86.9, 95.5)] mothers were either very happy or happy with the childbirth care received at the facility. CONCLUSION: Essential newborn care interventions were not universally available. Quality of care varied by health facility and type of intervention. Training and supervision using the Field Guide could improve newborn outcomes.

Concordance between estimates of acute malnutrition measured by weight-for-height and by mid-upper arm circumference after age adjustment: population-representative surveys from humanitarian settings.

BACKGROUND: Mid-upper arm circumference (MUAC) and weight-for-height (WHZ) are commonly used indicators to identify acute malnutrition. However, MUAC and WHZ diagnose different children, and produce prevalence estimates that are meaningfully different. Previous research in Somalia has suggested improved concordance using MUAC-for-age (MUACZ) rather than MUAC. We further evaluate the relationship between MUACZ, MUAC, and WHZ using surveys conducted globally. METHODS: We analyzed 882 population representative surveys from 41 countries. Children ages 6-59 months were classified as acutely malnourished using three independent criteria: WHZ < - 2 (WHZ2), MUAC< 125 mm (MUAC125), MUACZ < - 2 (MUACZ2). Population prevalence using each of the three criteria are presented by country and region. Correlations of survey prevalence for each indicator pair were assessed. Multivariable regression models of MUACZ and MUAC125 adjusted for WHZ2, stunting prevalence, age, and sex. To evaluate individual level diagnostic concordance, we compared the proportion of children identified by each of the three criteria. RESULTS: Median prevalence of acute malnutrition overall was highest for MUACZ2 (14.0%) followed by WHZ2 (10.6%), and lowest for MUAC125 (7.3%). The absolute difference in prevalence between MUACZ2 and WHZ2 was smaller than the difference between MUAC125 and WHZ2 for 51.3% of surveys. The correlations of WHZ2 with both MUACZ2 as well as with MUAC125 were weak, positive associations (Pearson's r = 0.5757 and 0.4943, respectively), but MUAC125 and MUACZ2 had a strong, linear relationship (Pearson's r = 0.9265). The adjusted regression model for MUACZ2 had greater fit (R2 = 0.50) relative to the adjusted model for MUAC125 (R2 = 0.43). The proportion of children identified by both MUAC125 and WHZ2 was 25.5%, smaller than the proportion identified by both MUACZ2 and WHZ2 (30.6%). CONCLUSIONS: MUACZ identified more children as malnourished than MUAC, resulting in a higher prevalence of acute malnutrition in nearly all settings. Prevalence by MUACZ was not consistently more similar to WHZ than that estimated by MUAC, and correlations with WHZ were only slightly improved relative to MUAC. Consequently, programmatic use of MUACZ cannot be justified based on improved concordance with WHZ. Further research on morbidity and mortality of children with low MUACZ only are needed before recommending MUACZ for wider use.