Overcoming denominator problems in refugee settings with fragmented electronic records for health and immigration data: a prediction-based approach.

BACKGROUND: Epidemiological studies in refugee settings are often challenged by the denominator problem, i.e. lack of population at risk data. We develop an empirical approach to address this problem by assessing relationships between occupancy data in refugee centres, number of refugee patients in walk-in clinics, and diseases of the digestive system. METHODS: Individual-level patient data from a primary care surveillance system (PriCarenet) was matched with occupancy data retrieved from immigration authorities. The three relationships were analysed using regression models, considering age, sex, and type of centre. Then predictions for the respective data category not available in each of the relationships were made. Twenty-one German on-site health care facilities in state-level registration and reception centres participated in the study, covering the time period from November 2017 to July 2021. RESULTS: 445 observations ("centre-months") for patient data from electronic health records (EHR, 230 mean walk-in clinics visiting refugee patients per month and centre; standard deviation sd: 202) of a total of 47.617 refugee patients were available, 215 for occupancy data (OCC, mean occupancy of 348 residents, sd: 287), 147 for both (matched), leaving 270 observations without occupancy (EHR-unmatched) and 40 without patient data (OCC-unmatched). The incidence of diseases of the digestive system, using patients as denominators in the different sub-data sets were 9.2% (sd: 5.9) in EHR, 8.8% (sd: 5.1) when matched, 9.6% (sd: 6.4) in EHR- and 12% (sd 2.9) in OCC-unmatched. Using the available or predicted occupancy as denominator yielded average incidence estimates (per centre and month) of 4.7% (sd: 3.2) in matched data, 4.8% (sd: 3.3) in EHR- and 7.4% (sd: 2.7) in OCC-unmatched. CONCLUSIONS: By modelling the ratio between patient and occupancy numbers in refugee centres depending on sex and age, as well as on the total number of patients or occupancy, the denominator problem in health monitoring systems could be mitigated. The approach helped to estimate the missing component of the denominator, and to compare disease frequency across time and refugee centres more accurately using an empirically grounded prediction of disease frequency based on demographic and centre typology. This avoided over-estimation of disease frequency as opposed to the use of patients as denominators.

Area-level socioeconomic deprivation, non-national residency, and Covid-19 incidence: A longitudinal spatiotemporal analysis in Germany.

Background: Socioeconomic conditions affect the dynamics of the Covid-19 pandemic. We analysed the association between area-level socioeconomic deprivation, proportion of non-nationals, and incidence of Covid-19 infections in Germany. Methods: Using linked nationally representative data at the level of 401 German districts from three waves of infection (January-2020 to May-2021), we fitted Bayesian spatiotemporal models to assess the association between socioeconomic deprivation, and proportion of non-nationals with Covid-19 incidence, controlling for age, sex, vaccination coverage, settlement structure, and spatial and temporal effects. We estimated risk ratios (RR) and corresponding 95% credible intervals (95% CrI). We further examined the deprivation domains (education, income, occupation), interactions between deprivation, sex and the proportion of non-nationals, and explored potential pathways from deprivation to Covid-19 incidence. Findings: Covid-19 incidence risk was 15% higher (RR=1·15, 95%-CrI=1·06-1·24) in areas classified with the highest deprivation quintile (Q5) compared to the least deprived areas (Q1). Medium-low (Q2), medium (Q3), and medium-high (Q4) deprived districts showed 6% (1·06, 1·00-1·12), 8% (1·08, 1·01-1·15), and 5% (1·05, 0·98-1·13) higher risk, respectively, compared to the least deprived. Districts with higher proportion of non-nationals showed higher incidence risk compared to districts with lowest proportion, but the association weakened across the three waves. During the first wave, an inverse association was observed with highest incidence risk in least deprived areas (Q1). Deprivation interacted with sex, but not with the proportion of non-nationals. Interpretation: Socioeconomic deprivation, and proportion of non-nationals are independently associated with the incidence of Covid-19. Regional planning of non-pharmaceutical interventions and vaccination strategies would benefit from consideration of area-level deprivation and non-national residency. Funding: The study was funded by the German Ministry of Health (ZMV I 1 - 25 20 COR 410).

Covid-19 pandemic policy monitor (COV-PPM) - European level tracking data of non-pharmaceutical interventions.

The Covid-19 Pandemic Policy Monitor (COV-PPM) dataset prospectively documents non-pharmaceutical interventions (NPIs) taken to contain SARS-Cov-2 transmission across countries in EU27, EEA and UK. In Germany, measures have also been recorded at the federal state and, partially, at the district levels. NPIs implemented since January 2020 have been retrieved and updated weekly from March 2020, from official governments webpages, Ministries of Health, National (Public) Health Institutes or Administrations. NPI categories collected refer to restrictions, closures or changes in functioning implemented in 13 domains: public events (gatherings in indoor or outdoor spaces); public institutions (kindergartens, schools, universities); public spaces (shops, bars, restaurants); public transport (trains, buses, trams, metro); citizens movement/mobility (e.g. pedestrians, cars, ships); border closures (air, land or sea, all incoming travels, from high-risk regions, only non-nationals); measures to improve the healthcare system (e.g. human resources or technical reinforcement, redistribution, material or infrastructural); measures for risk/vulnerable groups (e.g. elderly, chronically ill, pregnant); economic measures (e.g. lay-off rules establishment, actions to avoid job-loss, tax relaxation); testing policies (e.g. testing criteria changes); nose and mouth protection rules, vaccination and others/miscellaneous measures.

Monitoring the spatiotemporal epidemiology of Covid-19 incidence and mortality: A small-area analysis in Germany.

Timely monitoring of incidence risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated deaths at small-area level is essential to inform containment strategies. We analysed the spatiotemporal epidemiology of the SARSCoV- 2 pandemic at district level in Germany to develop a tool for disease monitoring. We used a Bayesian spatiotemporal model to estimate the district-specific risk ratios (RR) of SARS-CoV-2 incidence and the posterior probability (PP) for exceedance of RR thresholds 1, 2 or 3. Of 220 districts (55% of 401 districts) showing a RR > 1, 188 (47%) exceed the RR threshold with sufficient certainty (PP ≥ 80%) to be considered at high risk. 47 districts show very high (RR > 2, PP ≥ 80%) and 15 extremely high (RR > 3, PP ≥ 80%) risks. The spatial approach for monitoring the risk of SARS-CoV-2 provides an informative basis for local policy planning.

SARS-Cov-2 prevalence, transmission, health-related outcomes and control strategies in homeless shelters: Systematic review and meta-analysis.

BACKGROUND: People experiencing homelessness (PEH) may be at risk for COVID19. We synthesised evidence on SARS-Cov-2 infection, transmission, outcomes of disease, effects of non-pharmaceutical interventions (NPI), and the effectiveness of strategies for infection prevention and control (IPC). METHODS: Systematic review of articles, indexed in electronic databases (EMBASE, WHO-Covid19, Web of Science), institutional websites and the Norwegian Institute of Public Health's live map of COVID-19 evidence, and published from December 1st, 2019, to March 3rd, 2021. Empirical papers of any study design addressing Covid-19 and health(-related) outcomes in PEH or shelters' staff were included. (PROSPERO-2020-CRD42020187033). FINDINGS: Of 536 publications, 37 studies were included (two modelling, 31 observational, four qualitative studies). Random-effect meta-analysis yields a baseline SARS-Cov-2 prevalence of 2•32% (95% Confidence-Interval, 95%CI=1•30-3•34) in PEH and 1•55% (95%CI=0•79-2•31) in staff. In outbreaks, the pooled prevalence increases to 31•59% (95%CI=20•48-42•71) in PEH and 14•80% (95%CI=10•73-18•87) in staff. Main IPC strategies were universal rapid testing, expansion of non-congregate housing, and in-shelter measures (bed spacing, limited staff rotation, reduction in number of residents). INTERPRETATION: 32% of PEH and 15% staff are infected during outbreaks of SARS-Cov-2 in homeless shelters. Most studies were conducted in the USA. No studies were found quantifying health-related outcomes of NPI. Overview and evaluation of IPC strategies for PEH, a better understanding of disease transmission, and reliable data on PEH within Covid-19 notification systems are needed. Qualitative studies may serve to voice PEH and shelter staff experiences, and guide future evaluations and IPC strategies. FUNDING: None.

SARS-CoV-2 among migrants and forcibly displaced populations: A rapid systematic review.

The economic and health consequences of the COVID-19 pandemic pose a particular threat to vulnerable groups, such as migrants, particularly forcibly displaced populations. The aim of this review is (i) to synthesize the evidence on risk of infection and transmission among migrants, refugees, asylum seekers and internally displaced populations, and (ii) the effect of lockdown measures on these populations. We searched MEDLINE and WOS, preprint servers, and pertinent websites between 1st December 2019 and 26th June 2020. The included studies showed a high heterogeneity in study design, population, outcome and quality. The incidence risk of SARS-CoV-2 varied from 0•12% to 2•08% in non-outbreak settings and from 5•64% to 21•15% in outbreak settings. Migrants showed a lower hospitalization rate compared to non-migrants. Negative impacts on mental health due to lockdown measures were found across respective studies. However, findings show a tenuous and heterogeneous data situation, showing the need for more robust and comparative study designs.

Socioeconomic deprivation is inversely associated with measles incidence: a longitudinal small-area analysis, Germany, 2001 to 2017.

BackgroundAlthough measles is endemic throughout the World Health Organization European Region, few studies have analysed socioeconomic inequalities and spatiotemporal variations in the disease's incidence.AimTo study the association between socioeconomic deprivation and measles incidence in Germany, while considering relevant demographic, spatial and temporal factors.MethodsWe conducted a longitudinal small-area analysis using nationally representative linked data in 401 districts (2001-2017). We used spatiotemporal Bayesian regression models to assess the potential effect of area deprivation on measles incidence, adjusted for demographic and geographical factors, as well as spatial and temporal effects. We estimated risk ratios (RR) for deprivation quintiles (Q1-Q5), and district-specific adjusted relative risks (ARR) to assess the area-level risk profile of measles in Germany.ResultsThe risk of measles incidence in areas with lowest deprivation quintile (Q1) was 1.58 times higher (95% credible interval (CrI): 1.32-2.00) than in those with highest deprivation (Q5). Areas with medium-low (Q2), medium (Q3) and medium-high deprivation (Q4) had higher adjusted risks of measles relative to areas with highest deprivation (Q5) (RR: 1.23, 95%CrI: 0.99-1.51; 1.05, 95%CrI: 0.87-1.26 and 1.23, 95%CrI: 1.05-1.43, respectively). We identified 54 districts at medium-high risk for measles (ARR > 2) in Germany, of which 22 were at high risk (ARR > 3).ConclusionSocioeconomic deprivation in Germany, one of Europe's most populated countries, is inversely associated with measles incidence. This association persists after demographic and spatiotemporal factors are considered. The social, spatial and temporal patterns of elevated risk require targeted public health action and policy to address the complexity underlying measles epidemiology.

Health monitoring of refugees in reception centres for asylum seekers: Decentralized surveillance network for the analysis of routine medical data.

Refugees and asylum seekers living in reception centres tend to be not adequately included in population-based studies, routine medical data and official statistics. As part of the research project 'Health and primary-care sentinel surveillance in reception- and accommodation-centres for asylum-seekers in Germany' (PriCare), a health-monitoring approach was developed for the secondary use of routine medical data from on-site outpatient clinics in reception centres. To this end, a software application (Refugee Care Manager, RefCare©) for the digitisation and harmonisation of medical records was designed and implemented in reception centres in three German federal states. The approach of distributed computing in a surveillance network allows for the decentralised, harmonised analysis of the routine medical data stored in RefCare© in a manner that fully complies with data protection regulations and circumvents the need for centralised data storage. RefCare© provides an integrated surveillance feature that enables analyses of 64 indicators on population, morbidity, healthcare processes and quality of care to be undertaken across multiple facilities. This article describes the conceptual and practical approach and the technical procedures put in place to do so, and provides examples of the results that have been gained so far.

What is the evidence on availability and integration of refugee and migrant health data in health information systems in the WHO European Region?

The recent rapid increases in population movements across borders highlight the importance of reliable data on refugee and migrant health for public health planning. This scoping report examined evidence on the availability and integration of refugee and migrant health data in health information systems in the WHO European Region. Refugee and migrant health data were available in 25 of the Region’s 53 Member States, but differences existed in the availability, data types and main sources of data collection. Except for countries with population registers, the predominant data sources were medical records, disease-specific records and notification data. Data integration was often limited, and health monitoring surveys and data linkage approaches were underused. Policy considerations include harmonizing migrant definitions, promoting the coordination/governance of data collection, performance monitoring for health information systems, promoting cross-country exchange of experiences, exploiting data linkage, expanding existing health surveillance, reducing health-care barriers and strengthening general health information systems.

What is the evidence on availability and integration of refugee and migrant health data in health information systems in the WHO European Region? Themed issues on migration and health, X

The Health Evidence Network (HEN) is an information service for public health decision-makers in the WHO European Region, in action since 2003 and initiated and coordinated by the WHO Regional Office for Europe under the umbrella of the WHO European Health Information Initiative (a multipartner network coordinating all health information activities in the WHO European Region). HEN supports public health decision-makers to use the best available evidence in their own decisionmaking and aims to ensure links between evidence, health policies and improvements in public health. The HEN synthesis report series provides summaries of what is known about the policy issue, the gaps in the evidence and the areas of debate. Based on the synthesized evidence, HEN proposes policy considerations, not recommendations, for policy-makers to formulate their own recommendations and policies within their national context