1
|
Arena PJ, Bandak J, Jeon CY, Gadoth A, Hoff NA, Nkamba DM, Nianogo RA, Belin TR, Nielsen-Saines K, Kaba D, Rimoin AW. The impact of COVID-19 mitigation measures on neonatal health outcomes in sub-Saharan Africa: A systematic review and meta-analysis. Public Health 2025; 238:108-116. [PMID: 39642534 PMCID: PMC11929597 DOI: 10.1016/j.puhe.2024.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 10/19/2024] [Accepted: 11/28/2024] [Indexed: 12/09/2024]
Abstract
OBJECTIVES To assess the relationship between COVID-19 mitigation measures and stillbirth, low birth weight (LBW), and preterm birth (PTB) in sub-Saharan Africa. STUDY DESIGN Systematic review/meta-analysis. METHODS We searched six databases for literature indexed from January 2020 to December 2022 for studies examining COVID-19 policies and neonatal outcomes in sub-Saharan Africa. These studies were assessed for their risk of bias and described via narrative synthesis. Meta-analysis with random effects was performed to generate risk ratios (RRs) that were stratified by study scope to explore heterogeneity. RESULTS Our search identified 515 unique studies, sixteen of which were included. Most studies were multi-/single-center examinations (n = 7) and national/regional investigations (n = 6). The stillbirth RR suggested a marginal increase during mitigation measures (RR: 1.13; 95 % CI: 0.97, 1.31); however, among national/regional studies, there was no increase (RR: 0.96; 95 % CI: 0.82, 1.14). Similarly, the LBW RR suggested an increase during mitigation measures (RR: 1.18; 95 % CI: 0.90, 1.56), but the RR among national/regional investigations indicated no increase (RR: 0.97; 95 % CI: 0.91, 1.04). For PTB, the RR indicated no increase during mitigation measures (RR: 1.00; 95 % CI: 0.94, 1.07); there were no differences between multi-/single-center examinations and national/regional investigations. CONCLUSIONS Our results suggest that outcome risk did not change after mitigation measures were imposed when focusing on national/regional investigations and provide insights for both African health officials and researchers.
Collapse
Affiliation(s)
- Patrick J Arena
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
| | - Jane Bandak
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Christie Y Jeon
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA; Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Adva Gadoth
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Nicole A Hoff
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Dalau Mukadi Nkamba
- Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Roch A Nianogo
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA; California Center for Population Research, University of California Los Angeles, Los Angeles, CA, USA
| | - Thomas R Belin
- Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Karin Nielsen-Saines
- Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Didine Kaba
- Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Anne W Rimoin
- Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
2
|
Isse SA, Doğan A, Ali TA, Wehlie JA, Adam AA, Öztürk H. Hand Hygiene Compliance and Its Associated Factors Among Health Care Workers at Mogadishu Somali Turkiye Recep Tayyip Erdoğan Training and Research in a Tertiary Care Hospital. Risk Manag Healthc Policy 2024; 17:2415-2425. [PMID: 39429694 PMCID: PMC11490245 DOI: 10.2147/rmhp.s481057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 10/04/2024] [Indexed: 10/22/2024] Open
Abstract
Background Hand hygiene is a critical preventive measure for controlling infections, particularly in underdeveloped nations. Materials and Methods A cross-sectional study was conducted in a hospital in Mogadishu, Somalia, from January to March 2024. This study aimed to assess compliance with hand hygiene practices and related factors among healthcare professionals. Results The study population comprised 52% men and 47.3% women. Most participants held bachelor's degrees, with the majority being nurses or midwives. A significant proportion had over five years of work experience. Almost all participants were knowledgeable about hand hygiene. Most reported cleaning and drying their hands before, during, and after contact with bodily fluids during aseptic procedures. Age, gender, educational status, marriage, working experience, type of occupation, receiving hand hygiene training and knowledge, and having the availability of water, soap, alcohol, and gloves significantly affected the overall uptake of infection control measures in Mogadishu (p<0.05). Conclusion The findings highlight an urgent need for targeted interventions to enhance hand hygiene practices in Somalia. Addressing training gaps and resource shortages is crucial for reducing infection rates and safeguarding patient health in this high-risk setting.
Collapse
Affiliation(s)
- Suad Abdikarim Isse
- Department of Infectıon Preventıon Control, Mogadıshu Somalı Turkıye Recep Tayyıp Erdogan Traınıng and Research Hospıtal, Mogadishu, Somalia
| | - Ahmet Doğan
- Department of Infectious Diseases and Clinical Microbiology, Abant Izzet Baysal University Faculty of Medicine, Bolu, Turkiye
| | - Tigad Abdisad Ali
- Department of Infectıon Preventıon Control, Mogadıshu Somalı Turkıye Recep Tayyıp Erdogan Traınıng and Research Hospıtal, Mogadishu, Somalia
| | | | - Abdirahim Ali Adam
- Department of Infectious Diseases and Clinical Microbiology, Mogadishu-Somalia-Turkiye Recep Tayyip Erdoğan Training and Research Hospital, Mogadishu, Somalia
| | - Hüsna Öztürk
- Department of Infectious Control Nurse Istanbul Koşuyolu Yüksek İhtisas Eğitim ve Araştırma Hastanesi, Istanbul, Turkiye
| |
Collapse
|
3
|
Mugeni R, Ruranga C, Mutezimana E, Nishimwe A, Nzabanita J, Masabo E, Akili V, Twizeyimana L, Bahati O, Uwimana A, Musabanabaganwa C, Semakula M, Rukundo G, Jansen S, Mukamana L, Rubagiza J, Twagirumukiza M. Assessing factors associated with compliance to preventive measures of COVID-19 in Rwanda: a cross-sectional community survey. BMJ Open 2024; 14:e078610. [PMID: 39053965 PMCID: PMC11284918 DOI: 10.1136/bmjopen-2023-078610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 07/05/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVE To assess the level of compliance with COVID-19 preventive measures and compliance-associated factors in the Rwanda community. DESIGN Cross-sectional study. SETTINGS Country-wide community survey in Rwanda. PARTICIPANTS 4763 participants were randomly sampled following the sampling frame used for the recent Rwanda Demographic Health Survey. Participants were aged between 22 years and 94 years. OUTCOMES The participants' compliance with three preventive measures (wearing a face mask, washing hands and social distancing) was the main outcome. METHODS From 14 February 2022 to 27 February 2022, a cross-sectional survey using telephone calls was conducted. Study questionnaires included different questions such as participants' demographics and compliance with COVID-19 preventives measures. Verbal consent was obtained from each participant. The compliance on three main preventive measures (wearing a mask, washing hands and social distancing) were the main outcomes. Univariate and multivariable logistic regression analyses were performed to evaluate factors associated with compliance (age, gender, level of education, socioeconomic status). RESULTS Compliance with the three primary preventive measures (washing hands 98%, wearing a mask 97% and observing social distance 98%) was at a rate of 95%. The respondents' mean age was 46±11 SD (range 22-98) years. In addition, 69% were female and 86% had attended primary education. Bivariate and regression analyses indicated a significant association among the three primary preventive measures (p<0.05). The results showed factors associated significantly between the different models (p<0.05): proper mask use and social distancing in the hand washing model; hand washing, social distancing, avoiding handshakes and not attending gatherings in the proper mask use model; hand washing and avoiding handshakes in the social distancing model. CONCLUSION Compliance with the three key preventive measures against COVID-19 was high in the Rwandan community and these measures were interdependent. Therefore, the importance of all three measures should be emphasised for effective disease control.
Collapse
Affiliation(s)
- Regine Mugeni
- Kibagabaga Level Two Teaching Hospital, Republic of Rwanda Ministry of Health, Kigali, Rwanda
| | - Charles Ruranga
- University of Rwanda, Kigali, Rwanda
- College of Business and Economics, University of Rwanda, Kigali, Rwanda
- African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda
| | - Elias Mutezimana
- University of Rwanda, Kigali, Rwanda
- African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda
| | - Aurore Nishimwe
- Regional Alliance for Sustainable Development, Kigali, Rwanda
- College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Joseph Nzabanita
- University of Rwanda, Kigali, Rwanda
- College of Science and Technology, University of Rwanda, Kigali, Rwanda
| | - Emmanuel Masabo
- University of Rwanda, Kigali, Rwanda
- African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda
- College of Science and Technology, University of Rwanda, Kigali, Rwanda
| | - Viviane Akili
- Regional Alliance for Sustainable Development, Kigali, Rwanda
- Single Project Implementation Unit (SPIU), University of Rwanda, Kigali, Rwanda
| | - Laurence Twizeyimana
- Regional Alliance for Sustainable Development, Kigali, Rwanda
- Single Project Implementation Unit (SPIU), University of Rwanda, Kigali, Rwanda
| | - Odile Bahati
- Regional Alliance for Sustainable Development, Kigali, Rwanda
- Single Project Implementation Unit (SPIU), University of Rwanda, Kigali, Rwanda
| | | | | | - Muhamed Semakula
- Rwanda Biomedical Center, Ministry of Health, Kigali, Rwanda
- Centre for Statistics, Hasselt Biostatistics and statistical Bioinformatics Center, Hasselt University, Diepenbeek, Limburg, Belgium
| | - Gilbert Rukundo
- Rwanda Biomedical Center, Ministry of Health, Kigali, Rwanda
| | - Stefan Jansen
- College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Liberata Mukamana
- University of Rwanda, Kigali, Rwanda
- College of Business and Economics, University of Rwanda, Kigali, Rwanda
| | - Jolly Rubagiza
- University of Rwanda, Kigali, Rwanda
- Center for Gender Studies, University of Rwanda, Kigali, Rwanda
| | - Marc Twagirumukiza
- University of Rwanda, Kigali, Rwanda
- College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
- Faculty of Medicine and Health Sciences, Ghent University, Gent, Belgium
| |
Collapse
|
4
|
Htun YM, Maung NL, Ko DK, Htut HM, Phyo MK, Aung WL, Zaw HK, Min AK, Kyaw AP, Swe T, Zaw KK, Win KSN, Ko KK, Thaw KM, Aung SP, Aung SY, Htun SS, Paing SH, Htun SL, Naing ZM, Htun ZK, Naung H, Oo HH, Hla NY, San AK, Myat HM, Htet PS, Mon MK, Paing YM, Phyo WL, Paing WK, Rein T, Oo TL, Zaw TP, Oo TL, Thu TM, Aung TT, Soe HH, Soe AK, Oo AM, Aung A, Aung PP, Kyaw HA, Kyaw HP, Soe YNM, Ko MM, Aung ZK, Aung KT, Lwin YPC, Yan W, Soe PT, Htet ZL, Sint NH, Aung Z, Winn ZT, Thu KS, Shan NH, Htun NS, Win TT, Tun KM. Adherence to COVID-19 preventive measures among residents in selected townships, Yangon Region, Myanmar: a community-based cross-sectional study. Trop Med Health 2024; 52:36. [PMID: 38734710 PMCID: PMC11088027 DOI: 10.1186/s41182-024-00603-6] [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: 03/15/2024] [Accepted: 05/02/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND To fight the current coronavirus disease (COVID-19) pandemic, many countries have implemented various mitigation measures to contain the spread of the disease. By engaging with health service providers, the community's participation in adherence to preventive measures is certainly required in the implementation of COVID-19 mitigation strategies. Therefore, this study aimed to assess the level of adherence to COVID-19 preventive measures and its associated factors among the residents, Yangon Region, Myanmar. METHODS A community-based cross-sectional study was carried out among 636 residents in Yangon Region, Myanmar, from October to December 2021. A multistage non-probability sampling method, purposively selected for three townships in Yangon Region and convenience sampling for 212 participants from each township, was applied and the data were collected by face-to-face interviews using structured and pretested questionnaires. Data were entered, coded, and analyzed using IBM SPSS version 25.0. Simple and multiple logistic regression analysis were performed to identify the significant variables of adherence to COVID-19 preventive measures. RESULTS As a level of adherence to COVID-19 preventive measures, the proportion of residents who had good adherence was 39.3% (95% CI 35.5-43.2%), moderate adherence was 37.6% (95% CI 33.8-41.5%), and poor adherence was 23.1% (95% CI 19.9-26.6%). The age group of 31-40 years (AOR: 3.13, 95% CI 1.62-6.05), 30 years and younger (AOR: 3.22, 95% CI 1.75-5.92), Burmese ethnicity (AOR: 2.52, 95% CI 1.44-4.39), own business (AOR: 3.19, 95% CI 1.15-8.87), high school education level and below (AOR: 1.64, 95% CI 1.02-2.69), less than 280.90 USD of monthly family income (AOR: 1.51, 95% CI 1.01-2.29), low knowledge about COVID-19 (AOR: 1.90, 95% CI 1.26-2.88) were significantly associated with poor adherence to COVID-19 preventive measures. CONCLUSIONS In this study, nearly one-fourth of the residents were experiencing poor adherence to COVID-19 preventive measures. Therefore, building up the risk communication through the community using widely used mainstream media, the continuation of disease surveillance and announcement of updated information or advice for the public to increase awareness towards COVID-19, and enforcement to follow the recommended directions and regulations of health institutions are vital to consider for improving the adherence to preventive measures against COVID-19 among the residents.
Collapse
Affiliation(s)
- Ye Minn Htun
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar.
| | - Nyan Lin Maung
- Department of Research and Development, Defence Services Medical School, Yangon, Myanmar
| | - Dwe Kyaw Ko
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Han Myo Htut
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Min Khant Phyo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Wai Lynn Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Hein Khant Zaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Kyaw Min
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Phyo Kyaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thet Swe
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Kaung Khant Zaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Kyaw Swar Naing Win
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Khant Ko Ko
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Khant Min Thaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Saw Pyae Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Saw Yan Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Soe San Htun
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Soe Htet Paing
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Soe Lin Htun
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Zaw Myo Naing
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Zin Ko Htun
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Htoo Naung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Htun Htun Oo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Naing Ye Hla
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Kyaw San
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Hpone Myint Myat
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Phone Shan Htet
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Min Khant Mon
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Ye Myat Paing
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Wai Lin Phyo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Win Khant Paing
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thu Rein
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thit Lwin Oo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thet Paing Zaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thet Lynn Oo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Thint Myat Thu
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Than Toe Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Hein Htet Soe
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Kyaw Soe
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Myint Oo
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Aung Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Pyae Phyo Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Htun Aung Kyaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Hpone Pji Kyaw
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Yan Naing Myint Soe
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Myint Myat Ko
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Zin Ko Aung
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Kyaw Thiha Aung
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Yan Paing Chit Lwin
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Wai Yan
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Phyo Tayza Soe
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Zin Linn Htet
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Nay Hein Sint
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Zayar Aung
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Zin Thu Winn
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Kaung Si Thu
- Department of Prevention and Research Development of Hepatitis, AIDS and Other Viral Diseases, Health and Disease Control Unit, Nay Pyi Taw, 15011, Myanmar
| | - Nyan Htet Shan
- Outpatient Department, No. 1 Military Hospital (500 Bedded), Meiktila, Mandalay, Myanmar
| | - Nyan Sint Htun
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Tun Tun Win
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| | - Kyaw Myo Tun
- Department of Preventive and Social Medicine, Defence Services Medical Academy, Yangon, Myanmar
| |
Collapse
|
6
|
Katsiroumpa A, Sourtzi P, Kaitelidou D, Siskou O, Konstantakopoulou O, Galanis P. Predictors of Seasonal Influenza Vaccination Willingness among High-Risk Populations Three Years after the Onset of the COVID-19 Pandemic. Vaccines (Basel) 2023; 11:331. [PMID: 36851209 PMCID: PMC9963446 DOI: 10.3390/vaccines11020331] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
High-risk populations are at increased risk of severe influenza-related illness, hospitalization, and death due to influenza. The aim of our study was to assess the willingness of high-risk populations to take the influenza vaccine for the 2022-2023 season, and to investigate the factors associated with such willingness. We conducted a cross-sectional study in Greece in September 2022 using a convenience sample. We considered demographic characteristics, COVID-19-related variables, resilience, social support, anxiety, depression, and COVID-19-related burnout as potential predictors. Among participants, 39.4% were willing to accept the seasonal influenza vaccine, 33.9% were unwilling, and 26.8% were hesitant. Multivariable analysis identified that increased age and increased family support were associated with increased influenza vaccination willingness. Moreover, participants that have received COVID-19 booster doses were more willing to accept the influenza vaccine. In contrast, adverse effects because of COVID-19 vaccination and exhaustion due to measures against COVID-19 reduced influenza vaccination willingness. We found that the intention of high-risk populations to receive the influenza vaccine was low. Our study contributes to an increased understanding of the factors that affect vaccination willingness. Public health authorities could use this information to update vaccination programs against influenza. Emphasis should be given on safety and effectiveness issues.
Collapse
Affiliation(s)
- Aglaia Katsiroumpa
- Clinical Epidemiology Laboratory, Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Panayota Sourtzi
- Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Daphne Kaitelidou
- Center for Health Services Management and Evaluation, Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Olga Siskou
- Department of Tourism Studies, University of Piraeus, 18534 Piraeus, Greece
| | - Olympia Konstantakopoulou
- Center for Health Services Management and Evaluation, Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Petros Galanis
- Clinical Epidemiology Laboratory, Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens, Greece
| |
Collapse
|