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Meulman I, Uiters E, Cloin M, Struijs J, Polder J, Stadhouders N. From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands. THE EUROPEAN JOURNAL OF HEALTH ECONOMICS : HEPAC : HEALTH ECONOMICS IN PREVENTION AND CARE 2024:10.1007/s10198-024-01680-4. [PMID: 38499952 DOI: 10.1007/s10198-024-01680-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 01/25/2024] [Indexed: 03/20/2024]
Abstract
INTRODUCTION The COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands. METHODOLOGY This retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results. RESULTS Among the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result. DISCUSSION Our findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.
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Affiliation(s)
- Iris Meulman
- Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
- Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands.
| | - Ellen Uiters
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Mariëlle Cloin
- Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands
| | - Jeroen Struijs
- Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center-Health Campus The Hague, The Hague, The Netherlands
| | - Johan Polder
- Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands
- Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - Niek Stadhouders
- Scientific Center for Quality of Healthcare, Radboud University Medical Center, Nijmegen, The Netherlands
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Mennis E, Hobus M, van den Muijsenbergh M, van Loenen T. COVID-19 related morbidity and mortality in people experiencing homelessness in the Netherlands. PLoS One 2024; 19:e0296754. [PMID: 38315711 PMCID: PMC10843097 DOI: 10.1371/journal.pone.0296754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 12/13/2023] [Indexed: 02/07/2024] Open
Abstract
INTRODUCTION People who are homeless might be more at risk for getting infected by the SARS-COV-2 virus or for experiencing severe course of the infection due to their often more fragile health, unmet health needs, and poorer living conditions. This study aims to gain insight into the morbidity and mortality of the SARS-COV-2 virus among the homeless population in the Netherlands. METHODS In this observational retrospective study, anonymized data about patients experiencing homelessness who contacted a street doctor were gathered in nine cities in the Netherlands from March 2020 until March 2021. Data included patient characteristics, COVID-19 -related symptoms, diagnosis, and disease course of a SARS-COV-2 infection. RESULTS Of the total 1419 patients in whom 1544 COVID-19 related consults were registered, 16% tested positive for a SARS-COV-2 infection, and an additional 12% were clinically suspected of having a SARS-COV-2 infection but were seen before there were any COVID-19 tests available in General Practice or for some other reason not tested. Significantly more (p = <0.001) patients born outside the European Union tested positive for a SARS-COV-2 infection (36%) compared to the remainder of the population (20%). The most discerning symptom for being tested positive was loss of taste and smell (29% vs 6% in the negative tested group and 2% in the suspected group), fever (24% vs 13% in the negative tested group but 18% in the suspected group), and headache (26% vs 17% resp 14%), and fatigue (29% vs 20 resp 17%). Cough, dyspnea and common cold were more often seen in the clinically suspected but not tested group). Of the group that tested positive for a SARS-COV-2 infection, 10% were hospitalized. Two patients were admitted to intensive care and one patient died. Of patients who were clinically suspected of a SARS-COV-2 infection, 5% were hospitalized. CONCLUSION COVID-19 was not widespread among people experiencing homelessness in the Netherlands, but the number of hospitalizations in this study was relatively high. Monitoring this population during a pandemic is necessary to take prompt action when needed.
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Affiliation(s)
- Eline Mennis
- Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Michelle Hobus
- Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Maria van den Muijsenbergh
- Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands
- Pharos, Centre of Expertise on Health Disparities, Utrecht, The Netherlands
| | - Tessa van Loenen
- Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands
- Pharos, Centre of Expertise on Health Disparities, Utrecht, The Netherlands
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Vigil-De Gracia P, Delgado I, Saban E, Vigil-Vargas P, Cerrud-Rodríguez RC. COVID-19 epidemic in Panama. Heliyon 2024; 10:e23630. [PMID: 38187277 PMCID: PMC10767380 DOI: 10.1016/j.heliyon.2023.e23630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 01/09/2024] Open
Abstract
Objective It is necessary to establish the evolution that the pandemic has had in Panama by weeks and months and to clearly establish the existence of surges or peaks, according to cases and deaths and the relationship with age groups. Methodology We conducted a retrospective cohort study of all confirmed COVID-19 cases reported by the Ministry of Health of Panama during the first 3 years of the epidemic (March 9, 2020, March 11, 2023). All cases were obtained from information provided by the Ministry of Health. We obtained daily information of the population at the national level reported as new cases, deaths, admission to hospitals, admission to intensive care units and by age groups. The information is classified by epidemiological week and by month from the diagnosis of the first case until March 2023. Results During the three years of the study, 1,032,316 cases of COVID-19 were registered in the Republic of Panama, and the number of deaths reported was 8,621, for a fatality rate of 0.83 % throughout that period. The number of deaths decreased over the 3 years of the pandemic; however, similar to the cases, there were periods of surges (peaks) per year in June/July and in December/January. The lethality progressively increased according to the age of the affected patients. During the first year, the lethality in those under 20 years of age was 0.05 %, and in those over 80 years old, it was 17.54 %. This pattern was maintained during the second year; however, there was a large decrease in all age groups. Conclusion the highest lethality rate in Panama occurred in the first year of the pandemic, with a great decrease in the third year; the impact of lethality is proportional to the age of the individual, with a high possibility of death in those over 80 years of age. During each pandemic year, there are two peaks (surges of new cases and deaths) per year, which are important times to take into account to generate strategies aimed at reducing the impact.
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Affiliation(s)
- Paulino Vigil-De Gracia
- Complejo Hospitalario Dr. AAM Caja de Seguro Social, SIN/SENACYT, Transistmica, Bella Vista, Panama
| | | | | | | | - Roberto C. Cerrud-Rodríguez
- Vascular Medicine Outcomes (VAMOS) Program, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
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Wit FW, Reiss P, Rijnders B, Rokx C, Roukens A, Brinkman K, van der Valk M. COVID-19 in people with HIV in the Netherlands. AIDS 2023; 37:1671-1681. [PMID: 37199566 PMCID: PMC10399951 DOI: 10.1097/qad.0000000000003597] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/03/2023] [Accepted: 12/20/2022] [Indexed: 05/19/2023]
Abstract
OBJECTIVES We investigated occurrence of and risk factors for severe COVID-19 outcomes in people with HIV (PWH) in the Netherlands. DESIGN An ongoing prospective nationwide HIV cohort study. METHODS COVID-19 diagnoses and outcomes with other relevant medical information were prospectively collected from electronic medical records in all HIV treatment centers in the Netherlands, from the start of the COVID-19 epidemic until December 31, 2021. Risk factors for COVID-19 related hospitalization and death were investigated using multivariable logistic regression, including demographics, HIV-related factors, and comorbidities. RESULTS The cohort comprises 21 289 adult PWH, median age 51.2 years, 82% male, 70% were of Western origin, 12.0% were of sub-Saharan African and 12.6% Latin American/Caribbean origin, 96.8% had HIV-RNA less than 200 copies/ml, median CD4 + cell count 690 (IQR 510-908) cells/μl. Primary SARS-CoV-2 infections were registered in 2301 individuals, of whom 157 (6.8%) required hospitalization and 27 (1.2%) ICU admission. Mortality rates were 13 and 0.4% among hospitalized and nonhospitalized individuals, respectively. Independent risk factors for severe outcomes (COVID-19-related hospitalization and death) were higher age, having multiple comorbidities, a CD4 + cell count less than 200 cells/μl, uncontrolled HIV replication, and prior AIDS diagnosis. Migrants from sub-Saharan Africa, Latin America, and the Caribbean were at an increased risk of severe outcomes independently of other risk factors. CONCLUSION In our national cohort of PWH, risk of severe COVID-19 outcomes was increased in individuals with uncontrolled HIV replication, low CD4 + cell count, and prior AIDS diagnosis, independently of general risk factors such as higher age, comorbidity burden and migrants originating from non-Western countries.
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Affiliation(s)
- Ferdinand W.N.M. Wit
- Stichting HIV Monitoring
- Amsterdam University Medical Centers, University of Amsterdam, Department of Infectious Diseases, Amsterdam Infection & Immunity Institute, Amsterdam
| | - Peter Reiss
- Stichting HIV Monitoring
- Amsterdam University Medical Centers, University of Amsterdam, Department of Infectious Diseases, Amsterdam Infection & Immunity Institute, Amsterdam
| | - Bart Rijnders
- Erasmus University Medical Center, Departments of Internal Medicine & Medical Microbiology, Rotterdam
| | - Casper Rokx
- Erasmus University Medical Center, Departments of Internal Medicine & Medical Microbiology, Rotterdam
| | - Anna Roukens
- Leiden University Medical Center, Department of Internal Medicine, Leiden
| | - Kees Brinkman
- Onze Lieve Vrouwe Gasthuis, Department of Internal Medicine, Amsterdam, Netherlands
| | - Marc van der Valk
- Stichting HIV Monitoring
- Amsterdam University Medical Centers, University of Amsterdam, Department of Infectious Diseases, Amsterdam Infection & Immunity Institute, Amsterdam
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Pijpers J, van Roon A, van Roekel C, Labuschagne L, Smagge B, Ferreira JA, de Melker H, Hahné S. Determinants of COVID-19 Vaccine Uptake in The Netherlands: A Nationwide Registry-Based Study. Vaccines (Basel) 2023; 11:1409. [PMID: 37766087 PMCID: PMC10537724 DOI: 10.3390/vaccines11091409] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/18/2023] [Accepted: 08/19/2023] [Indexed: 09/29/2023] Open
Abstract
By September 2022, the uptake of at least one dose of COVID-19 vaccine in the Dutch adult population was 84%. Ecological studies have indicated a lower uptake in certain population groups. We aimed to investigate determinants of COVID-19 vaccine uptake in the Netherlands at individual level to evaluate and optimize implementation of the vaccination program and generate hypotheses for research on drivers of, and barriers to, vaccination. A retrospective database study was performed including the entire Dutch population ≥ 18. Vaccination data (5 January 2021-18 November 2021) were at individual levels linked to sociodemographic data. Random forest analyses ranked sociodemographic determinants of COVID-19 vaccine uptake. The most important determinant was age; uptake increased until the age of 80 (67% in 18-35 years, 92% in 67-79 years, and 88% in those > 80). Personal income and socioeconomic position ranked second and third, followed by migration status. Uptake was lower among individuals in the lowest income group (69%), those receiving social benefits (56%), and individuals with two parents born abroad (59%). Our finding that age is the most important determinant for uptake likely reflects the prioritisation of elderly in the programme and the general understanding of their increased vulnerability. However, our findings also reveal important other disparities in vaccine uptake. How to best address this inequity in future vaccination campaigns requires further research.
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Affiliation(s)
- Joyce Pijpers
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Annika van Roon
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Caren van Roekel
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Lisanne Labuschagne
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Bente Smagge
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - José A. Ferreira
- Statistics and Modelling, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Hester de Melker
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
| | - Susan Hahné
- Epidemiology and Surveillance, National Institute for Public Health and the Environment, 3721 MA De Bilt, The Netherlands
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de Boer PT, van de Kassteele J, Vos ERA, van Asten L, Dongelmans DA, van Gageldonk‐Lafeber AB, den Hartog G, Hofhuis A, van der Klis F, de Lange DW, Stoeldraijer L, de Melker HE, Geubbels E, van den Hof S, Wallinga J. Age-specific severity of severe acute respiratory syndrome coronavirus 2 in February 2020 to June 2021 in the Netherlands. Influenza Other Respir Viruses 2023; 17:e13174. [PMID: 37621921 PMCID: PMC10444602 DOI: 10.1111/irv.13174] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/23/2023] [Accepted: 06/28/2023] [Indexed: 08/26/2023] Open
Abstract
Background The severity of Severe Acute Respiratory Syndrome Coronavirus 2 infection varies with age and time. Here, we quantify how age-specific risks of hospitalization, intensive care unit (ICU) admission, and death upon infection changed from February 2020 to June 2021 in the Netherlands. Methods A series of large representative serology surveys allowed us to estimate age-specific numbers of infections in three epidemic periods (late-February 2020 to mid-June 2020, mid-June 2020 to mid-February 2021, and mid-February 2021 to late-June 2021). We accounted for reinfections and breakthrough infections. Severity measures were obtained by combining infection numbers with age-specific numbers of hospitalization, ICU admission, and excess all-cause deaths. Results There was an accelerating, almost exponential, increase in severity with age in each period. The rate of increase with age was the highest for death and the lowest for hospitalization. In late-February 2020 to mid-June 2020, the overall risk of hospitalization upon infection was 1.5% (95% confidence interval [CI] 1.3-1.8%), the risk of ICU admission was 0.36% (95% CI: 0.31-0.42%), and the risk of death was 1.2% (95% CI: 1.0-1.4%). The risk of hospitalization was significantly increased in mid-June 2020 to mid-February 2021, while the risk of ICU admission remained stable over time. The risk of death decreased over time, with a significant drop among ≥70-years-olds in mid-February 2021 to late-June 2021; COVID-19 vaccination started early January 2021. Conclusion Whereas the increase in severity of Severe Acute Respiratory Syndrome Coronavirus 2 with age remained stable, the risk of death upon infection decreased over time. A significant drop in risk of death among elderly coincided with the introduction of COVID-19 vaccination.
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Affiliation(s)
- Pieter T. de Boer
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Jan van de Kassteele
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Eric R. A. Vos
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Liselotte van Asten
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Dave A. Dongelmans
- Department of Intensive Care MedicineAmsterdam UMC (location AMC)AmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | | | - Gerco den Hartog
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
- Laboratory of Medical ImmunologyRadboudumcNijmegenThe Netherlands
| | - Agnetha Hofhuis
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Fiona van der Klis
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Dylan W. de Lange
- Intensive Care, University Medical Center UtrechtUniversity of UtrechtUtrechtThe Netherlands
| | | | | | - Hester E. de Melker
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Eveline Geubbels
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Susan van den Hof
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
| | - Jacco Wallinga
- Center for Infectious Disease ControlNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
- Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
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7
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Generaal E, van Santen DKD, Campman SL, Booij MJ, Price D, Buster M, van Dijk C, Boyd A, Bruisten SM, van Dam AP, van der Lubben M, van Duijnhoven YTHP, Prins M. Low prevalence of current and past SARS-CoV-2 infections among visitors and staff members of homelessness services in Amsterdam at the end of the second wave of infections in the Netherlands. PLoS One 2023; 18:e0288610. [PMID: 37490469 PMCID: PMC10368265 DOI: 10.1371/journal.pone.0288610] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 07/02/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND People experiencing homelessness (PEH) may be at increased risk of SARS-CoV-2 infection and severe COVID-19. The Dutch government established emergency shelters and introduced preventive measures for homelessness services. There were no major SARS-CoV-2 outbreaks noticed among PEH during the first two waves of infections. This study aimed to assess the prevalence of current and past infections among PEH and staff by conducting an on-site COVID-19 screening project at homelessness services in Amsterdam, the Netherlands. METHODS We assessed the proportion of visitors and staff members of four homelessness services at two locations in Amsterdam with positive SARS-CoV-2 qPCR and antibody results (IgG/IgM Rapid Test/Biozek) in May 2021. We also assessed sociodemographic, clinical and lifestyle characteristics, compliance with basic prevention measures and intention to vaccinate against COVID-19 among PEH and staff. RESULTS A total of 138 visitors and 53 staff members filled out a questionnaire and were tested. Among PEH, the SARS-CoV-2 positivity rate was 0% (0/133;95%CI = 0-1.9) and the antibody positivity rate was 1.6% (2/131;95%CI = 0.8-7.5) among those without prior COVID-19 vaccination. Among staff, these percentages were 3% (1/32;95%CI = 0.1-16.2) and 11% (5/53;95%CI = 3.6-23.6), respectively. Most participants were often compliant with the basic preventive measures 'not shaking hands', 'wearing a face mask' and 'washing hands', but not with 'physical distancing'. High vaccination intent was more common among staff members (55%) than among visitors (42%), while high trust in the governmental COVID-19 policies was more common among visitors (41%) than among staff (30%). CONCLUSIONS We observed a low prevalence of past and current SARS-CoV-2 infections among PEH, which may be explained by instated shelter policies, limited daily activities of PEH and compliance with prevention measures. Vaccine hesitancy and mistrust among visitors and staff could hinder vaccination uptake, suggesting that interventions towards homelessness services are needed.
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Affiliation(s)
- Ellen Generaal
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- National Institute for Public Health and the Environment (RIVM), Centre for Infectious Disease Control (Cib), Bilthoven, the Netherlands
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - D K Daniela van Santen
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
- Department of Disease Elimination, Burnet Institute, Melbourne, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - Sophie L Campman
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
| | - Marjolein J Booij
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
| | - Dylan Price
- Public Health Service of Amsterdam, Amsterdam, the Netherlands
| | - Marcel Buster
- Public Health Service of Amsterdam, Amsterdam, the Netherlands
| | | | - Anders Boyd
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
- Stichting HIV Monitoring, Amsterdam, the Netherlands
| | - Sylvia M Bruisten
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
- Public Health Service of Amsterdam, Amsterdam, the Netherlands
| | - Alje P van Dam
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
- Public Health Service of Amsterdam, Amsterdam, the Netherlands
| | | | - Yvonne T H P van Duijnhoven
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Public Health Service of Rotterdam, Rotterdam, the Netherlands
| | - Maria Prins
- Department of Infectious Diseases, Research and Prevention, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC Location University of Amsterdam, Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Infection and Immunity, Infectious Diseases, Amsterdam, the Netherlands
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8
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Chilunga FP, Campman S, Galenkamp H, Boyd A, Bolijn R, Leenstra T, Agyemang C, Uiters E, Prins M, Stronks K. Relative contributions of pre-pandemic factors and intra-pandemic activities to differential COVID-19 risk among migrant and non-migrant populations in the Netherlands: lessons for future pandemic preparedness. Int J Equity Health 2023; 22:127. [PMID: 37403097 DOI: 10.1186/s12939-023-01936-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 06/18/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND Although risk factors for differences in SARS-CoV-2 infections between migrant and non-migrant populations in high income countries have been identified, their relative contributions to these SARS-CoV-2 infections, which could aid in the preparation for future viral pandemics, remain unknown. We investigated the relative contributions of pre-pandemic factors and intra-pandemic activities to differential SARS-CoV-2 infections in the Netherlands by migration background (Dutch, African Surinamese, South-Asian Surinamese, Ghanaians, Turkish, and Moroccan origin). METHODS We utilized pre-pandemic (2011-2015) and intra-pandemic (2020-2021) data from the HELIUS cohort, linked to SARS-CoV-2 PCR test results from Public Health Service of Amsterdam (GGD Amsterdam). Pre-pandemic factors included socio-demographic, medical, and lifestyle factors. Intra-pandemic activities included COVID-19 risk aggravating and mitigating activities such as physical distancing, use of face masks, and other similar activities. We calculated prevalence ratios (PRs) in the HELIUS population that was merged with GGD Amsterdam PCR test data using robust Poisson regression (SARS-CoV-2 PCR test result as outcome, migration background as predictor). We then obtained the distribution of migrant and non-migrant populations in Amsterdam as of January 2021 from Statistics Netherlands. The migrant populations included people who have migrated themselves as well as their offspring. We used PRs and the population distributions to calculate population attributable fractions (PAFs) using the standard formula. We used age and sex adjusted models to introduce pre-pandemic factors and intra-pandemic activities, noting the relative changes in PAFs. RESULTS From 20,359 eligible HELIUS participants, 8,595 were linked to GGD Amsterdam PCR test data and included in the study. Pre-pandemic socio-demographic factors (especially education, occupation, and household size) resulted in the largest changes in PAFs when introduced in age and sex adjusted models (up to 45%), followed by pre-pandemic lifestyle factors (up to 23%, especially alcohol consumption). Intra-pandemic activities resulted in the least changes in PAFs when introduced in age and sex adjusted models (up to 16%). CONCLUSION Interventions that target pre-pandemic socio-economic status and other drivers of health inequalities between migrant and non-migrant populations are urgently needed at present to better prevent infection disparities in future viral pandemics.
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Affiliation(s)
- Felix P Chilunga
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands.
| | - Sophie Campman
- Department of Infectious Diseases, Public Health Service Amsterdam (GGD Amsterdam), Amsterdam, The Netherlands
- Department of Infectious Diseases, Amsterdam Infection, and Immunity (AII), Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Henrike Galenkamp
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands
| | - Anders Boyd
- Department of Infectious Diseases, Public Health Service Amsterdam (GGD Amsterdam), Amsterdam, The Netherlands
- Stichting HIV Monitoring, Amsterdam, The Netherlands
| | - Renee Bolijn
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands
| | - Tjalling Leenstra
- Department of Infectious Diseases, Public Health Service Amsterdam (GGD Amsterdam), Amsterdam, The Netherlands
- Centre for Infectious Disease Control, National Coordination Centre for Communicable Disease Control, National Institute for Public Health, and the Environment, Bilthoven, The Netherlands
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands
| | - Ellen Uiters
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Maria Prins
- Department of Infectious Diseases, Public Health Service Amsterdam (GGD Amsterdam), Amsterdam, The Netherlands
- Department of Infectious Diseases, Amsterdam Infection, and Immunity (AII), Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Karien Stronks
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands
- Centre for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
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Chilunga FP, Appelman B, van Vugt M, Kalverda K, Smeele P, van Es J, Wiersinga WJ, Rostila M, Prins M, Stronks K, Norredam M, Agyemang C. Differences in incidence, nature of symptoms, and duration of long COVID among hospitalised migrant and non-migrant patients in the Netherlands: a retrospective cohort study. THE LANCET REGIONAL HEALTH. EUROPE 2023; 29:100630. [PMID: 37261215 PMCID: PMC10079482 DOI: 10.1016/j.lanepe.2023.100630] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 06/02/2023]
Abstract
Background Comprehensive data on long COVID across ethnic and migrant groups are lacking. We investigated incidence, nature of symptoms, clinical predictors, and duration of long COVID among COVID-19 hospitalised patients in the Netherlands by migration background (Dutch, Turkish, Moroccan, and Surinamese origin, Others). Methods We used COVID-19 admissions and follow up data (January 2021-July 2022) from Amsterdam University Medical Centers. We calculated long COVID incidence proportions per NICE guidelines by migration background and assessed for clinical predictors via robust Poisson regressions. We then examined associations between migration background and long COVID using robust Poisson regressions and adjusted for derived clinical predictors, and other biologically relevant factors. We also assessed long COVID symptom persistence at one-year post-discharge. Findings 1886 patients were included. 483 patients had long COVID (26%, 95% CI 24-28%) at 12 weeks post-discharge. Symptoms like dizziness, joint pain, insomnia, and headache varied by migration background. Clinical predictors of long COVID were female sex, hospital admission duration, intensive care unit admission, and receiving oxygen, or corticosteroid therapy. Long COVID risk was higher among patients with migration background than Dutch origin patients after adjustments for derived clinical predictors, age, smoking, vaccination status, comorbidities and remdesivir treatment. Only 14% of long COVID symptoms persisted at one-year post-discharge. Interpretation There are significant differences in occurrence, nature of symptoms, and duration of long COVID by migration background. Studies assessing the spectrum of functional limitation and access to post-COVID healthcare are needed to help plan for appropriate and accessible healthcare interventions. Funding The Amsterdam UMC COVID-19 biobank is supported by the Amsterdam UMC Corona Research Fund and the Talud Foundation (Stichting Talud). The current analyses were supported by the Novo Nordisk Foundation [NNF21OC0067528].
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Affiliation(s)
- Felix Patience Chilunga
- Department of Public and Occupational Health, Amsterdam Public Health, University of Amsterdam Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Brent Appelman
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, Amsterdam Institute for Infection and Immunity (AII), University of Amsterdam, Amsterdam, The Netherlands
| | - Michele van Vugt
- Division of Infectious Diseases, Amsterdam University Medical Centers, Location AMC, Amsterdam Institute for Infection and Immunity (AII), University of Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Kirsten Kalverda
- Department Pulmonary Medicine, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Patrick Smeele
- Department Pulmonary Medicine, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Josien van Es
- Department Pulmonary Medicine, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Willem Joost Wiersinga
- Center for Experimental and Molecular Medicine, Amsterdam University Medical Centers, Amsterdam Institute for Infection and Immunity (AII), University of Amsterdam, Amsterdam, The Netherlands
- Division of Infectious Diseases, Amsterdam University Medical Centers, Location AMC, Amsterdam Institute for Infection and Immunity (AII), University of Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Mikael Rostila
- Department of Public Health Sciences, Stockholm University, Stockholm, Sweden
- Centre for Health Equity Studies, Stockholm University/Karolinska Institutet, Stockholm, Sweden
| | - Maria Prins
- Division of Infectious Diseases, Amsterdam University Medical Centers, Location AMC, Amsterdam Institute for Infection and Immunity (AII), University of Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands
| | - Karien Stronks
- Department of Public and Occupational Health, Amsterdam Public Health, University of Amsterdam Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Centre for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
| | - Marie Norredam
- Section for Health Services Research, Department of Public Health, Research Centre for Migration, Ethnicity and Health (MESU), University of Copenhagen, Copenhagen, Denmark
- Department of Infectious Diseases, Copenhagen University Hospital, Amager and Hvidovre, University of Copenhagen, Copenhagen, Denmark
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health, University of Amsterdam Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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van Boven M, Hetebrij WA, Swart A, Nagelkerke E, van der Beek RF, Stouten S, Hoogeveen RT, Miura F, Kloosterman A, van der Drift AMR, Welling A, Lodder WJ, de Roda Husman AM. Patterns of SARS-CoV-2 circulation revealed by a nationwide sewage surveillance programme, the Netherlands, August 2020 to February 2022. Euro Surveill 2023; 28:2200700. [PMID: 37347416 PMCID: PMC10288829 DOI: 10.2807/1560-7917.es.2023.28.25.2200700] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 03/16/2023] [Indexed: 06/23/2023] Open
Abstract
BackgroundSurveillance of SARS-CoV-2 in wastewater offers a near real-time tool to track circulation of SARS-CoV-2 at a local scale. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable and can be left-censored.AimWe aimed to infer latent virus loads in a comprehensive sewage surveillance programme that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population.MethodsWe applied a multilevel Bayesian penalised spline model to estimate time- and STP-specific virus loads based on water flow-adjusted SARS-CoV-2 qRT-PCR data for one to four sewage samples per week for each of the more than 300 STPs.ResultsThe model captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day variation in the measurements. Estimated STP virus loads varied by more than two orders of magnitude, from ca 1012 virus particles per 100,000 persons per day in the epidemic trough in August 2020 to almost 1015 per 100,000 in many STPs in January 2022. The timing of epidemics at the local level was slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level.ConclusionAlthough substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 that is performed at high sampling frequency can track long-term progression of an epidemic at a local scale in near real time.
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Affiliation(s)
- Michiel van Boven
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Wouter A Hetebrij
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Arno Swart
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Erwin Nagelkerke
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Rudolf Fhj van der Beek
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Sjors Stouten
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Rudolf T Hoogeveen
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Fuminari Miura
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Center for Marine Environmental Studies (CMES), Ehime University, Ehime, Japan
| | - Astrid Kloosterman
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Centre for Environmental Safety and Security, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Anne-Merel R van der Drift
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Anne Welling
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Willemijn J Lodder
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Ana Maria de Roda Husman
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Institute for Risk Assessment Science (IRAS), Utrecht University, Utrecht, the Netherlands
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11
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Intent to vaccinate against SARS-CoV-2 and its determinants across six ethnic groups living in Amsterdam, the Netherlands: A cross-sectional analysis of the HELIUS study. Vaccine 2023; 41:2035-2045. [PMID: 36803902 PMCID: PMC9922586 DOI: 10.1016/j.vaccine.2023.02.030] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 12/19/2022] [Accepted: 02/09/2023] [Indexed: 02/15/2023]
Abstract
BACKGROUND Ethnic minority groups experience a disproportionately high burden of infections, hospitalizations and mortality due to COVID-19, and therefore should be especially encouraged to receive SARS-CoV-2 vaccination. This study aimed to investigate the intent to vaccinate against SARS-CoV-2, along with its determinants, in six ethnic groups residing in Amsterdam, the Netherlands. METHODS We analyzed data of participants enrolled in the population-based multi-ethnic HELIUS cohort, aged 24 to 79 years, who were tested for SARS-CoV-2 antibodies and answered questions on vaccination intent from November 23, 2020 to March 31, 2021. During the study period, SARS-CoV-2 vaccination in the Netherlands became available to individuals working in healthcare or > 75 years old. Vaccination intent was measured by two statements on a 7-point Likert scale and categorized into low, medium, and high. Using ordinal logistic regression, we examined the association between ethnicity and lower vaccination intent. We also assessed determinants of lower vaccination intent per ethnic group. RESULTS A total of 2,068 participants were included (median age 56 years, interquartile range 46-63). High intent to vaccinate was most common in the Dutch ethnic origin group (369/466, 79.2%), followed by the Ghanaian (111/213, 52.1%), South-Asian Surinamese (186/391, 47.6%), Turkish (153/325, 47.1%), African Surinamese (156/362, 43.1%), and Moroccan ethnic groups (92/311, 29.6%). Lower intent to vaccinate was more common in all groups other than the Dutch group (P < 0.001). Being female, believing that COVID-19 is exaggerated in the media, and being < 45 years of age were common determinants of lower SARS-CoV-2 vaccination intent across most ethnic groups. Other identified determinants were specific to certain ethnic groups. CONCLUSIONS Lower intent to vaccinate against SARS-CoV-2 in the largest ethnic minority groups of Amsterdam is a major public health concern. The ethnic-specific and general determinants of lower vaccination intent observed in this study could help shape vaccination interventions and campaigns.
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12
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Impact of the COVID-19 Outbreak-Delayed Referral of Colorectal and Lung Cancer in Primary Care: A National Retrospective Cohort Study. Cancers (Basel) 2023; 15:cancers15051462. [PMID: 36900257 PMCID: PMC10000463 DOI: 10.3390/cancers15051462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/14/2023] [Accepted: 02/20/2023] [Indexed: 03/02/2023] Open
Abstract
The Coronavirus disease 2019 (COVID-19) outbreak impacted health care. We investigated its impact on the time to referral and diagnosis for symptomatic cancer patients in The Netherlands. We performed a national retrospective cohort study utilizing primary care records linked to The Netherlands Cancer Registry. For patients with symptomatic colorectal, lung, breast, or melanoma cancer, we manually explored free and coded texts to determine the durations of the primary care (IPC) and secondary care (ISC) diagnostic intervals during the first COVID-19 wave and pre-COVID-19. We found that the median IPC duration increased for colorectal cancer from 5 days (Interquartile Range (IQR) 1-29 days) pre-COVID-19 to 44 days (IQR 6-230, p < 0.01) during the first COVID-19 wave, and for lung cancer, the duration increased from 15 days (IQR) 3-47) to 41 days (IQR 7-102, p < 0.01). For breast cancer and melanoma, the change in IPC duration was negligible. The median ISC duration only increased for breast cancer, from 3 (IQR 2-7) to 6 days (IQR 3-9, p < 0.01). For colorectal cancer, lung cancer, and melanoma, the median ISC durations were 17.5 (IQR (9-52), 18 (IQR 7-40), and 9 (IQR 3-44) days, respectively, similar to pre-COVID-19 results. In conclusion, for colorectal and lung cancer, the time to primary care referral was substantially prolonged during the first COVID-19 wave. In such crises, targeted primary care support is needed to maintain effective cancer diagnosis.
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13
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Chilunga FP, Stoeldraijer L, Agyemang C, Stronks K, Harmsen C, Kunst AE. Inequalities in COVID-19 deaths by migration background during the first wave, interwave period and second wave of the COVID-19 pandemic: a closed cohort study of 17 million inhabitants of the Netherlands. J Epidemiol Community Health 2022; 77:jech-2022-219521. [PMID: 36316152 DOI: 10.1136/jech-2022-219521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 10/05/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND It is not known how differences in COVID-19 deaths by migration background in the Netherlands evolved throughout the pandemic, especially after introduction of COVID-19 prevention measures targeted at populations with a migration background (in the second wave). We investigated associations between migration background and COVID-19 deaths across first wave of the pandemic, interwave period and second wave in the Netherlands. METHODS We obtained multiple registry data from Statistics Netherlands spanning from 1 March 2020 to 14 March 2021 comprising 17.4 million inhabitants. We estimated incidence rate ratios for COVID-19 deaths by migration background using Poisson regression models and adjusted for relevant sociodemographic factors. RESULTS Populations with a migration background, especially those with Turkish, Moroccan and Surinamese background, exhibited higher risk of COVID-19 deaths than the Dutch origin population throughout the study periods. The elevated risk of COVID-19 deaths among populations with a migration background (as compared with Dutch origin population) was around 30% higher in the second wave than in the first wave. CONCLUSIONS Differences in COVID-19 deaths by migration background persisted in the second wave despite introduction of COVID-19 prevention measures targeted at populations with a migration background in the second wave. Research on explanatory mechanisms and novel prevention measures are needed to address the ongoing differences in COVID-19 deaths by migration background.
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Affiliation(s)
- Felix P Chilunga
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam 1105 AZ, The Netherlands
| | | | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam 1105 AZ, The Netherlands
| | - Karien Stronks
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam 1105 AZ, The Netherlands
| | | | - Anton E Kunst
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam 1105 AZ, The Netherlands
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14
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Grant MP, Helsper CW, Stellato R, van Erp N, van Asselt KM, Slottje P, Muris J, Brandenbarg D, de Wit NJ, van Gils CH. The Impact of the COVID Pandemic on the Incidence of Presentations with Cancer-Related Symptoms in Primary Care. Cancers (Basel) 2022; 14:cancers14215353. [PMID: 36358772 PMCID: PMC9656532 DOI: 10.3390/cancers14215353] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/24/2022] [Accepted: 10/27/2022] [Indexed: 12/02/2022] Open
Abstract
Simple Summary The coronavirus pandemic profoundly affected how patients access health care services, as many individuals attempted to minimise risks of infectious contact and reduce burdens on health systems. This study aims to explore the effects of the coronavirus pandemic on patient presentations for cancer-related symptoms in primary care. It utilises routine clinical data for 1.23 million people in the Netherlands, comparing the first year of the pandemic to the two years prior. These data identify a 34% reduction in the incidence of cancer-related symptoms during the first wave (March to June 2020), with overall incidence returning to pre-corona levels after this period. In the first wave, the incidence of many symptoms was substantially reduced: breast lump (−17%), haematuria (−15%), abdominal mass (−21%), tiredness (−45%), lymphadenopathy (−25%), and naevus (−37%). In the second wave (October 2020 to February 2021), the incidence of breast lump and rectal bleeding was increased (both +14%), and tiredness was decreased (−20%), with the majority of other symptoms being similar to pre-COVID levels. These data describe large-scale primary care avoidance that did not increase until the end of the first COVID year for many cancer-related symptoms, suggestive that substantial numbers of patients delayed presenting to primary care. Abstract Introduction: In the Netherlands, the onset of the coronavirus pandemic saw shifts in primary health service provision away from physical consultations, cancer-screening programs were temporarily halted, and government messaging focused on remaining at home. In March and April 2020, weekly cancer diagnoses decreased to 73% of their pre-COVID levels, and 39% for skin cancer. This study aims to explore the effect of the COVID pandemic on patient presentations for cancer-related symptoms in primary care in The Netherlands. Methods: Retrospective cohort study using routine clinical primary care data. Monthly incidences of patient presentations for cancer-related symptoms in five clinical databases in The Netherlands were analysed from March 2018 to February 2021. Results: Data demonstrated reductions in the incidence of cancer-related symptom presentations to primary care during the first COVID wave (March-June 2020) of −34% (95% CI: −43 to −23%) for all symptoms combined. In the second wave (October 2020–February 2021) there was no change in incidence observed (−8%, 95% CI −20% to 6%). Alarm-symptoms demonstrated decreases in incidence in the first wave with subsequent incidences that continued to rise in the second wave, such as: first wave: breast lump −17% (95% CI: −27 to −6%) and haematuria −15% (95% CI −24% to −6%); and second wave: rectal bleeding +14% (95% CI: 0 to 30%) and breast lump +14% (95% CI: 2 to 27%). Presentations of common non-alarm symptom such as tiredness and naevus demonstrated decreased in-cidences in the first wave of 45% (95% CI: −55% to −33%) and 37% (95% CI −47% to −25%). In the second wave, tiredness incidence was reduced by 20% (95% CI: −33% to −3%). Subgroup analy-sis did not demonstrate difference in incidence according to sex, age groups, comorbidity status, or previous history of cancer. Conclusions: These data describe large-scale primary care avoidance that did not increase until the end of the first COVID year for many cancer-related symptoms, suggestive that substantial numbers of patients delayed presenting to primary care. For those patients who had underlying cancer, this may have had impacted the cancer stage at diagnosis, treatment, and mortality.
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Affiliation(s)
- Matthew P. Grant
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
- Correspondence:
| | - Charles W. Helsper
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Rebecca Stellato
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Nicole van Erp
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Kristel M. van Asselt
- Department of General Practice, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute Program, 1081 BT Amsterdam, The Netherlands
| | - Pauline Slottje
- Amsterdam Public Health Research Institute Program, 1081 BT Amsterdam, The Netherlands
- Department of General Practice, Amsterdam UMC Location Vrije Universiteit, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Jean Muris
- Department of General Practice, Maastricht University Care and Public Health Research Institute, 6200 MD Maastricht, The Netherlands
| | - Daan Brandenbarg
- Department of General Practice and Elderly Care Medicine, University Medical Centre Groningen, University of Groningen, 9712 CP Groningen, The Netherlands
| | - Niek J. de Wit
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Carla H. van Gils
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
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Ritsema F, Bosdriesz JR, Leenstra T, Petrignani MWF, Coyer L, Schreijer AJM, van Duijnhoven YTHP, van de Wijgert JHHM, Schim van der Loeff MF, Matser A. Factors Associated With Using the COVID-19 Mobile Contact-Tracing App Among Individuals Diagnosed With SARS-CoV-2 in Amsterdam, the Netherlands: Observational Study. JMIR Mhealth Uhealth 2022; 10:e31099. [PMID: 35867842 PMCID: PMC9407157 DOI: 10.2196/31099] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/22/2021] [Accepted: 04/04/2022] [Indexed: 11/19/2022] Open
Abstract
Background Worldwide, efforts are being made to stop the COVID-19 pandemic caused by SARS-CoV-2. Contact tracing and quarantining are key in limiting SARS-CoV-2 transmission. Mathematical models have shown that the time between infection, isolation of cases, and quarantining of contacts are the most important components that determine whether the pandemic can be controlled. Mobile contact-tracing apps could accelerate the tracing and quarantining of contacts, including anonymous contacts. However, real-world observational data on the uptake and determinants of contact-tracing apps are limited. Objective The aim of this paper is to assess the use of a national Dutch contact-tracing app among notified cases diagnosed with SARS-CoV-2 infection and investigate which characteristics are associated with the use of the app. Methods Due to privacy regulations, data from the app could not be used. Instead, we used anonymized SARS-CoV-2 routine contact-tracing data collected between October 28, 2020, and February 26, 2021, in the region of Amsterdam, the Netherlands. Complete case logistic regression analysis was performed to identify which factors (age, gender, country of birth, municipality, number of close contacts, and employment in either health care or education) were associated with using the app. Age and number of close contacts were modelled as B-splines due to their nonlinear relationship. Results Of 29,766 SARS-CoV-2 positive cases, 4824 (16.2%) reported app use. Median age of cases was 41 (IQR 29-55) years, and 46.7% (n=13,898) were male. In multivariable analysis, males (adjusted odds ratio [AOR] 1.11, 95% CI 1.04-1.18) and residents of municipalities surrounding Amsterdam were more likely to use the app (Aalsmeer AOR 1.34, 95% CI 1.13-1.58; Ouder-Amstel AOR 1.96, 95% CI 1.54-2.50), while people born outside the Netherlands, particularly those born in non-Western countries (AOR 0.33, 95% CI 0.30-0.36), were less likely to use the app. Odds of app use increased with age until the age of 58 years and decreased sharply thereafter (P<.001). Odds of app use increased with number of contacts, peaked at 8 contacts, and then decreased (P<.001). Individuals working in day care, home care, and elderly nursing homes were less likely to use the app. Conclusions Contact-tracing app use among people with confirmed SARS-CoV-2 infection was low in the region of Amsterdam. This diminishes the potential impact of the app by hampering the ability to warn contacts. Use was particularly low among older people, people born outside the Netherlands, and people with many contacts. Use of the app was also relatively low compared to those from some other European countries, some of which had additional features beyond contact tracing, making them potentially more appealing. For the Dutch contact-tracing app to have an impact, uptake needs to be higher; therefore, investing more into promotional efforts and additional features could be considered.
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Affiliation(s)
- Feiko Ritsema
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
| | - Jizzo R Bosdriesz
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
- Department of Internal Medicine, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Academic Medical Center, Amsterdam, Netherlands
| | - Tjalling Leenstra
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
| | | | - Liza Coyer
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
- Department of Internal Medicine, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Academic Medical Center, Amsterdam, Netherlands
| | - Anja J M Schreijer
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
| | | | - Janneke H H M van de Wijgert
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Maarten F Schim van der Loeff
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
- Department of Internal Medicine, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Academic Medical Center, Amsterdam, Netherlands
| | - Amy Matser
- Department of Infectious Diseases, GGD Amsterdam, Amsterdam, Netherlands
- Department of Internal Medicine, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Academic Medical Center, Amsterdam, Netherlands
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16
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Pan X, Kaminga AC, Chen Y, Liu H, Wen SW, Fang Y, Jia P, Liu A. Auxiliary Screening COVID-19 by Serology. Front Public Health 2022; 10:819841. [PMID: 35983367 PMCID: PMC9380738 DOI: 10.3389/fpubh.2022.819841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. Methods Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1st, 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. Results Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). Conclusion Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world.
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Affiliation(s)
- Xiongfeng Pan
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Atipatsa C. Kaminga
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
- Department of Mathematics and Statistics, Mzuzu University, Mzuzu, Malawi
| | - Yuyao Chen
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Hongying Liu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Shi Wu Wen
- OMNI Research Group, Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Obstetrics and Gynaecology, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada
- School of Epidemiology and Public Health, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada
| | - Yingjing Fang
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- *Correspondence: Peng Jia
| | - Aizhong Liu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
- Aizhong Liu
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Ghaznavi C, Eguchi A, Tanoue Y, Yoneoka D, Kawashima T, Suzuki M, Hashizume M, Nomura S. Pre- and post-COVID-19 all-cause mortality of Japanese citizens versus foreign residents living in Japan, 2015–2021. SSM Popul Health 2022; 18:101114. [PMID: 35601222 PMCID: PMC9118913 DOI: 10.1016/j.ssmph.2022.101114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 04/25/2022] [Accepted: 04/29/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Cyrus Ghaznavi
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Medical Education Program, Washington University School of Medicine in St Louis, Saint Louis, USA
| | - Akifumi Eguchi
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Center for Preventive Medical Sciences, Chiba University, Chiba, Japan
| | - Yuta Tanoue
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Institute for Business and Finance, Waseda University, Tokyo, Japan
| | - Daisuke Yoneoka
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Tokyo Foundation for Policy Research, Tokyo, Japan
- Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Takayuki Kawashima
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Mathematical and Computing Science, Tokyo Institute of Technology, Tokyo, Japan
| | - Motoi Suzuki
- Center for Surveillance, Immunization, and Epidemiologic Research, National Institute of Infectious Diseases, Tokyo, Japan
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shuhei Nomura
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Tokyo Foundation for Policy Research, Tokyo, Japan
- Corresponding author. Department of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
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18
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Verburgh ML, Boyd A, Wit FWNM, Schim van der Loeff MF, van der Valk M, Bakker M, Kootstra NA, van der Hoek L, Reiss P. Similar risk of SARS-CoV-2 infection and similar nucleocapsid antibody levels in people with well-controlled HIV and a comparable cohort of people without HIV. J Infect Dis 2021; 225:1937-1947. [PMID: 34929034 PMCID: PMC8755357 DOI: 10.1093/infdis/jiab616] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/16/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Within the ongoing AGEhIV Cohort Study in Amsterdam, we prospectively compared the incidence of and risk factors for SARS-CoV-2 infection between HIV-positive and -negative participants. Moreover, we compared SARS-CoV-2 nucleocapsid antibody levels between participants with incident infection from both groups. METHODS Starting in September 2020, consenting HIV-positive and HIV-negative participants were assessed 6-monthly for incident SARS-CoV-2 infection, using combined IgA/IgM/IgG SARS-CoV-2 nucleocapsid antibody assay. Cumulative incidence of SARS-CoV-2 infection and associated risk factors were assessed from February 27, 2020 through April 30, 2021 using complementary log-log regression. In those with incident SARS-CoV-2 infection, N-antibody levels were compared between groups using linear regression. RESULTS 241 HIV-positive (99.2% virally suppressed) and 326 HIV-negative AGEhIV participants were included in this study. Cumulative SARS-CoV-2 incidence by April 2021 was 13.4% and 11.6% in HIV-positive and HIV-negative participants, respectively (p=0.61). Younger age and African origin were independently associated with incident infection. In those with incident infection, only self-reported fever, but not HIV status, was associated with higher N-antibody levels. CONCLUSIONS HIV-positive individuals with suppressed viremia and adequate CD4 cell counts were had similar risk of SARS-CoV-2 acquisition, and had similar SARS-CoV-2 N-antibody levels following infection compared to a comparable cohort of HIV-negative people.
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Affiliation(s)
- Myrthe L Verburgh
- Amsterdam University Medical Centers, Department of Infectious Diseases, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands.,Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | - Anders Boyd
- HIV Monitoring Foundation, Amsterdam, The Netherlands.,Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Ferdinand W N M Wit
- Amsterdam University Medical Centers, Department of Infectious Diseases, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands.,HIV Monitoring Foundation, Amsterdam, The Netherlands
| | - Maarten F Schim van der Loeff
- Amsterdam University Medical Centers, Department of Infectious Diseases, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands.,Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Marc van der Valk
- Amsterdam University Medical Centers, Department of Infectious Diseases, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands.,HIV Monitoring Foundation, Amsterdam, The Netherlands
| | - Margreet Bakker
- Amsterdam University Medical Centers, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands
| | - Neeltje A Kootstra
- Amsterdam University Medical Centers, Department of Experimental Immunology, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands
| | - Lia van der Hoek
- Amsterdam University Medical Centers, Department of Medical Microbiology and Infection Prevention, Laboratory of Experimental Virology, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands
| | - Peter Reiss
- Amsterdam University Medical Centers, Department of Infectious Diseases, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands.,Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
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