Punam Mangtani

Background: The COVID-19 pandemic exposed the health equity gap between and within countries. Western countries were the first to receive vaccines and mortality was higher among socially deprived, minority and indigenous populations. Surprisingly, many sub-Saharan countries reported low excess mortalities. These countries share experiences with community organization and participation in health. The aim of this article was to analyse if and how this central role of people can promote a successful pandemic response. Methods: This analysis was partly based on local and national experiences shared during an international and Latin American conference on person-and people-centred care in 2021. Additionally, excess mortality data and pandemic control-relevant data, as well as literature on the pandemic response of countries with an unexpected low excess mortality were consulted. Results: Togo, Mongolia, Thailand and Kenya had a seven times lower mean excess mortality for 2020 and 2021 than the United States of America. More successful pandemic responses were observed in settings with experience in managing epidemics like Ebola and HIV, well-established community networks, a national philosophy of mutual aid, financial government assistance, more human resources for primary care and paid community health workers. Discussion: Since trust in authorities and health needs vary greatly, local strategies are needed to complement national and international pandemic responses. Three key levers were identified to promote locally-tailored pandemic management: well-organized communities, community-oriented primary care, and health information systems. An organized community structure stems from a shared ethical understanding of humanity as being interconnected with each other and the environment. This structure facilitates mutual aid and participation in decision making. Community-oriented primary care includes attention for collective community health and ways to improve health from its roots. A health information system supports collective health and health equity analysis by presenting health needs stratified for social deprivation, ethnicity, and community circumstances. Conclusions: The difference in excess mortality between countries during the COVID-19 pandemic and various country experiences demonstrate the potential of the levers in promoting a more just and effective health emergency response. These same levers and strategies can promote more inclusive and socially just health systems.

BACKGROUND: We examined fidelity and feasibility of implementation of COVID‐19 preventive measures in schools, and explored associations between adherence to these measures and staff well‐being, to inform policy on sustainable implementation and staff wellbeing.METHODS: Surveys were conducted across 128 schools in England with 107 headteachers and 2698 staff‐members with reference to autumn term 2020, examining school‐level implementation of preventive measures, adherence, and teacher burnout (response rates for headteacher and staff surveys were 84% and 59%, respectively).RESULTS: The median number of measures implemented in primary and secondary schools was 33 (range 23‐41), and 32 (range 22‐40), respectively; most measures presented challenges. No differences were found regarding number of measures implemented by school‐level socio‐economic disadvantage. High adherence was reported for staff wearing face‐coverings, staff regularly washing their hands, (secondary only) desks facing forwards, and (primary only) increased cleaning of surfaces and student hand‐washing. Adherence to most measures was reported as higher in primary than secondary schools. Over half of school leaders and 42% (517/1234) of other teaching staff suffered from high emotional exhaustion. Higher teacher‐reported school‐wide adherence with measures was consistently associated with lower burnout for leaders and other teaching staff.CONCLUSIONS: Findings indicate a tremendous effort in implementing preventive measures and an urgent need to support investments in improving teacher wellbeing.

Q fever represents an important ‘neglected zoonosis’, with high prevalences recorded across the Middle East region. Among rural desert-dwelling communities in the region, camel milk is largely consumed raw, due to perceptions of dromedaries as a uniquely clean livestock species mentioned in the Qur’an and Islamic hadith, while milk from other livestock species is usually boiled. As a result, camels present a unique public health threat among such communities from milk-borne pathogens, including C. burnetii . In view of this, an epidemiological survey was conducted among dromedary herds in southern Jordan between September 2017 and October 2018, including 404 camels from 121 randomly selected herds. In addition, 510 household members associated with these herds were interviewed regarding potential high-risk practices for zoonotic transmission. Weight adjusted camel population seroprevalence for C. burnetii was 49.6% (95% CI: 44.7 – 54.5), with evidence of maternally derived immunity in calves ≤6 months old. Adjusted herd-level prevalence was 76.0% (95%CI 72.7–80.2), with 30.4% (144/477) of individuals estimated to consume raw milk from infected herds monthly or more. Following multivariable logistic regression analysis, seropositive status in camels was found to be associated with increasing age, high herd tick burdens, keeping the herd together throughout the year including when calving, and owning larger (>50) sheep and goat flocks, with goats presenting a higher risk than sheep. Racing camel status was found to be protective. Socioculturally appropriate interventions aimed at raising awareness of potential risks associated with drinking raw camel milk, alongside appropriate livestock management interventions, should be considered.

Background: Population-based health surveys are typically conducted using face-to-face household interviews in low- and middle-income countries (LMICs). However, telephone-based surveys are cheaper, faster, and can provide greater access to hard-to-reach or remote populations. The rapid growth in mobile phone ownership in LMICs provides a unique opportunity to implement novel data collection methods for population health surveys. Objective: This study aims to describe the development and population representativeness of a mobile phone survey measuring live poultry exposure in urban Bangladesh. Methods: A population-based, cross-sectional, mobile phone survey was conducted between September and November 2019 in North and South Dhaka City Corporations (DCC), Bangladesh, to measure live poultry exposure using a stratified probability sampling design. Data were collected using a computer-assisted telephone interview platform. The call operational data were summarized, and the participant data were weighted by age, sex, and education to the 2011 census. The demographic distribution of the weighted sample was compared with external sources to assess population representativeness. Results: A total of 5486 unique mobile phone numbers were dialed, with 1047 respondents completing the survey. The survey had an overall response rate of 52.2% (1047/2006) and a co-operation rate of 89.0% (1047/1176). Initial results comparing the sociodemographic profile of the survey sample to the census population showed that mobile phone sampling slightly underrepresented older individuals and overrepresented those with higher secondary education. After weighting, the demographic profile of the sample population matched well with the latest DCC census population profile. Conclusions: Probability-based mobile phone survey sampling and data collection methods produced a population-representative sample with minimal adjustment in DCC, Bangladesh. Mobile phone–based surveys can offer an efficient, economic, and robust way to conduct surveillance for population health outcomes, which has important implications for improving population health surveillance in LMICs.

MERS-CoV Infection among Camel Populations, Jordan

Purpose: To describe the methods used to identify and validate congenital malformation diagnoses recorded in UK electronic health records, and the results of validation studies.Methods: Medline and Embase were searched for publications between 1987 and 2019 that involved identifying congenital malformations from UK electronic health records using diagnostic codes. The methods and code‐lists used to identify congenital malformations, and the methods and results of validations, were examined.Results: We retrieved 54 eligible studies; 36 identified congenital malformations from primary care data and 18 from secondary care data alone or in combination with birth and/or death records. Identification in secondary care data relied on codes from the ‘Q’ chapter for congenital malformations in ICD‐10. In contrast, studies using primary care data frequently used additional codes outside of the ‘P’ chapter for congenital malformation diagnoses in Read, although the exact codes used were not always clear. Eight studies validated diagnoses identified in primary care data. The positive predictive value was highest (80%–100%) for congenital malformations overall, major malformations, and heart defects although the validity of the reference standard used was often uncertain. It was lowest for neural tube defects (71%) and developmental hip dysplasia (56%).Conclusions: Studies identifying congenital malformations from primary care data provided limited details about the methods used. The few validation studies were limited to diagnoses recorded in primary care. Further assessments of all measures of validity in both data sources and of other malformation subgroups are needed, using robust reference standards and adhering to reporting guidelines.

BACKGROUND Population-based health surveys are typically conducted using face-to-face household interviews in low- and middle-income countries (LMICs). However, telephone-based surveys are cheaper, faster, and can provide greater access to hard-to-reach or remote populations. The rapid growth in mobile phone ownership in LMICs provides a unique opportunity to implement novel data collection methods for population health surveys. OBJECTIVE This study aims to describe the development and population representativeness of a mobile phone survey measuring live poultry exposure in urban Bangladesh. METHODS A population-based, cross-sectional, mobile phone survey was conducted between September and November 2019 in North and South Dhaka City Corporations (DCC), Bangladesh, to measure live poultry exposure using a stratified probability sampling design. Data were collected using a computer-assisted telephone interview platform. The call operational data were summarized, and the participant data were weighted by age, sex, and education to the 2011 census. The demographic distribution of the weighted sample was compared with external sources to assess population representativeness. RESULTS A total of 5486 unique mobile phone numbers were dialed, with 1047 respondents completing the survey. The survey had an overall response rate of 52.2% (1047/2006) and a co-operation rate of 89.0% (1047/1176). Initial results comparing the sociodemographic profile of the survey sample to the census population showed that mobile phone sampling slightly underrepresented older individuals and overrepresented those with higher secondary education. After weighting, the demographic profile of the sample population matched well with the latest DCC census population profile. CONCLUSIONS Probability-based mobile phone survey sampling and data collection methods produced a population-representative sample with minimal adjustment in DCC, Bangladesh. Mobile phone–based surveys can offer an efficient, economic, and robust way to conduct surveillance for population health outcomes, which has important implications for improving population health surveillance in LMICs.

Background: During the first wave of the influenza A(H1N1)pdm09 pandemic in England in 2009, morbidity and mortality were higher in patients of South Asian (Indian, Pakistani or Bangladeshi) ethnic minority groups.Objectives: This study aims to provide insights in the representation of this group among reported cases, indicating susceptibility and exposure.Methods: All laboratory‐confirmed cases including basic demographic and limited clinical information that were reported to the FluZone surveillance system between April and October 2009 were retrieved. Missing ethnicity data were imputed using the previously developed and validated South Asian Names and Group Recognition Algorithm (SANGRA). Differences between ethnic groups were calculated using chi‐square, log‐rank and t tests and rate ratios. Geographic clustering was compared using Ripley's K functions.Results: SANGRA identified 2447 (28%) of the total of 8748 reported cases as South Asian. South Asian cases were younger (P < .001), more often male (P = .002) and more often from deprived areas (P < .001) than cases of other ethnic groups. Time between onset of symptoms and laboratory sampling was longer in this group (P < .001), and they were less often advised antiviral treatment (P < .001), however, declined treatment less. The highest cumulative incidence was seen in the West Midlands region (32.7/10 000), London (7.0/10 000) and East of England region (5.7/10 000).Conclusions: People of South Asian ethnic groups were disproportionally affected by the first wave of the influenza pandemic in England in 2009. The findings presented contribute to further understanding of demographic, socioeconomic and ethnic factors of the outbreak and inform future influenza preparedness to ensure appropriate prevention and care.