Pub Date : 2024-02-14DOI: 10.3389/ijph.2024.1606557
Javier Muñoz Laguna
{"title":"Global Burden of Disease Estimates of Low Back Pain: Time to Consider and Assess Certainty?","authors":"Javier Muñoz Laguna","doi":"10.3389/ijph.2024.1606557","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606557","url":null,"abstract":"","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"57 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3389/ijph.2024.1606272
Krzysztof Kanecki, K. Lewtak, P. Tyszko, Irena Kosińska, Patryk Tarka, Paweł Goryński, A. Nitsch-Osuch
Objectives: There are limited data on the impact of the COVID-19 outbreak in Poland on newborn health. The aim of the study is to show recent information on hospitalizations of newborns in Poland in the pre-pandemic and COVID-19 pandemic era.Methods: A retrospective, population-based study was conducted using data from hospital discharge records of patients hospitalized in 2017–2021.Results: The data on which the study was based consisted of a substantial number of 104,450 hospitalization records. Annual hospitalization rate was estimated to be 50.3–51.9 per 1,000 in 2017–2019, 56 per 1,000 in 2020 and it rose to 77.7 per 1,000 in 2021. In comparison to the pre-pandemic period, in the COVID-19 era, we observed significantly more hospitalization cases of newborns affected by maternal renal and urinary tract diseases (p < 0.001), syndrome of infant of mother with gestational diabetes (p < 0.001), maternal complications of pregnancy (p < 0.001). In the COVID-19 era, the prevalence of COVID-19 among newborns was 4.5 cases per 1,000 newborn hospitalizations.Conclusion: The COVID-19 pandemic outbreak could significantly contribute to qualitative and quantitative changes in hospitalizations among newborns.
{"title":"Newborn Hospitalizations Before and During COVID-19 Pandemic in Poland: A Comparative Study Based on a National Hospital Registry","authors":"Krzysztof Kanecki, K. Lewtak, P. Tyszko, Irena Kosińska, Patryk Tarka, Paweł Goryński, A. Nitsch-Osuch","doi":"10.3389/ijph.2024.1606272","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606272","url":null,"abstract":"Objectives: There are limited data on the impact of the COVID-19 outbreak in Poland on newborn health. The aim of the study is to show recent information on hospitalizations of newborns in Poland in the pre-pandemic and COVID-19 pandemic era.Methods: A retrospective, population-based study was conducted using data from hospital discharge records of patients hospitalized in 2017–2021.Results: The data on which the study was based consisted of a substantial number of 104,450 hospitalization records. Annual hospitalization rate was estimated to be 50.3–51.9 per 1,000 in 2017–2019, 56 per 1,000 in 2020 and it rose to 77.7 per 1,000 in 2021. In comparison to the pre-pandemic period, in the COVID-19 era, we observed significantly more hospitalization cases of newborns affected by maternal renal and urinary tract diseases (p < 0.001), syndrome of infant of mother with gestational diabetes (p < 0.001), maternal complications of pregnancy (p < 0.001). In the COVID-19 era, the prevalence of COVID-19 among newborns was 4.5 cases per 1,000 newborn hospitalizations.Conclusion: The COVID-19 pandemic outbreak could significantly contribute to qualitative and quantitative changes in hospitalizations among newborns.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"24 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3389/ijph.2024.1606557
Javier Muñoz Laguna
{"title":"Global Burden of Disease Estimates of Low Back Pain: Time to Consider and Assess Certainty?","authors":"Javier Muñoz Laguna","doi":"10.3389/ijph.2024.1606557","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606557","url":null,"abstract":"","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"113 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139837439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3389/ijph.2024.1606591
Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri
Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.
{"title":"The Transformative Impact of Community-Led Monitoring in the South African Health System: A Comprehensive Analysis","authors":"Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri","doi":"10.3389/ijph.2024.1606591","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606591","url":null,"abstract":"Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"109 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3389/ijph.2023.1606491
B. Armocida, L. Monasta, S. Sawyer, F. Bustreo, G. Onder, G. Castelpietra, F. Pricci, Valentina Minardi, C. Giacomozzi, C. Abbafati, Lauryn K. Stafford, Maja Pašović, Simon I. Hay, Kanyin Lian Ong, P. Perel, David Beran
Objectives: As little is known about the burden of type 1 (T1DM) and type 2 diabetes (T2DM) in adolescents in Western Europe (WE), we aimed to explore their epidemiology among 10–24 year-olds.Methods: Estimates were retrieved from the Global Burden of Diseases Study (GBD) 2019. We reported counts, rates per 100,000 population, and percentage changes from 1990 to 2019 for prevalence, incidence and years lived with disability (YLDs) of T1DM and T2DM, and the burden of T2DM in YLDs attributable to high body mass index (HBMI), for 24 WE countries.Results: In 2019, prevalence and disability estimates were higher for T1DM than T2DM among 10–24 years old adolescents in WE. However, T2DM showed a greater increase in prevalence and disability than T1DM in the 30 years observation period in all WE countries. Prevalence increased with age, while only minor differences were observed between sexes.Conclusion: Our findings highlight the substantial burden posed by DM in WE among adolescents. Health system responses are needed for transition services, data collection systems, education, and obesity prevention.
{"title":"The Burden of Type 1 and Type 2 Diabetes Among Adolescents and Young Adults in 24 Western European Countries, 1990–2019: Results From the Global Burden of Disease Study 2019","authors":"B. Armocida, L. Monasta, S. Sawyer, F. Bustreo, G. Onder, G. Castelpietra, F. Pricci, Valentina Minardi, C. Giacomozzi, C. Abbafati, Lauryn K. Stafford, Maja Pašović, Simon I. Hay, Kanyin Lian Ong, P. Perel, David Beran","doi":"10.3389/ijph.2023.1606491","DOIUrl":"https://doi.org/10.3389/ijph.2023.1606491","url":null,"abstract":"Objectives: As little is known about the burden of type 1 (T1DM) and type 2 diabetes (T2DM) in adolescents in Western Europe (WE), we aimed to explore their epidemiology among 10–24 year-olds.Methods: Estimates were retrieved from the Global Burden of Diseases Study (GBD) 2019. We reported counts, rates per 100,000 population, and percentage changes from 1990 to 2019 for prevalence, incidence and years lived with disability (YLDs) of T1DM and T2DM, and the burden of T2DM in YLDs attributable to high body mass index (HBMI), for 24 WE countries.Results: In 2019, prevalence and disability estimates were higher for T1DM than T2DM among 10–24 years old adolescents in WE. However, T2DM showed a greater increase in prevalence and disability than T1DM in the 30 years observation period in all WE countries. Prevalence increased with age, while only minor differences were observed between sexes.Conclusion: Our findings highlight the substantial burden posed by DM in WE among adolescents. Health system responses are needed for transition services, data collection systems, education, and obesity prevention.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"12 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3389/ijph.2024.1606591
Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri
Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.
{"title":"The Transformative Impact of Community-Led Monitoring in the South African Health System: A Comprehensive Analysis","authors":"Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri","doi":"10.3389/ijph.2024.1606591","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606591","url":null,"abstract":"Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"45 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.3389/ijph.2024.1606807
Ifeanyi Okekearu, Onyinye Ojeh, Kenneth Okoineme, Jane Adizue, Yusuf H. Wada, Elizabeth Adeyemo, Jennifer Anyanti, Abdullahi Musa Yola, A. Umar
{"title":"Public-Private Sector Mix Approach to Achieving Effective, Efficient and Value-Added TB Programming in Nigeria: Lessons Learned","authors":"Ifeanyi Okekearu, Onyinye Ojeh, Kenneth Okoineme, Jane Adizue, Yusuf H. Wada, Elizabeth Adeyemo, Jennifer Anyanti, Abdullahi Musa Yola, A. Umar","doi":"10.3389/ijph.2024.1606807","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606807","url":null,"abstract":"","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"52 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.3389/ijph.2024.1606829
Yi Luo, Mimi Xiao
Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood.Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models.Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (β = −0.83, p < 0.01), educational attainment (β = −0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (β = −0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (β = −1.18, p < 0.01), educational attainment (β = −0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes.Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital.
{"title":"Early Weight Status and Human Capital in Adulthood: A 32-Year Follow-Up of the 1970 British Cohort Study","authors":"Yi Luo, Mimi Xiao","doi":"10.3389/ijph.2024.1606829","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606829","url":null,"abstract":"Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood.Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models.Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (β = −0.83, p < 0.01), educational attainment (β = −0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (β = −0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (β = −1.18, p < 0.01), educational attainment (β = −0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes.Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"114 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139840556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.3389/ijph.2024.1606829
Yi Luo, Mimi Xiao
Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood.Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models.Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (β = −0.83, p < 0.01), educational attainment (β = −0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (β = −0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (β = −1.18, p < 0.01), educational attainment (β = −0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes.Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital.
{"title":"Early Weight Status and Human Capital in Adulthood: A 32-Year Follow-Up of the 1970 British Cohort Study","authors":"Yi Luo, Mimi Xiao","doi":"10.3389/ijph.2024.1606829","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606829","url":null,"abstract":"Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood.Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models.Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (β = −0.83, p < 0.01), educational attainment (β = −0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (β = −0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (β = −1.18, p < 0.01), educational attainment (β = −0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes.Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"126 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.3389/ijph.2024.1606807
Ifeanyi Okekearu, Onyinye Ojeh, Kenneth Okoineme, Jane Adizue, Yusuf H. Wada, Elizabeth Adeyemo, Jennifer Anyanti, Abdullahi Musa Yola, A. Umar
{"title":"Public-Private Sector Mix Approach to Achieving Effective, Efficient and Value-Added TB Programming in Nigeria: Lessons Learned","authors":"Ifeanyi Okekearu, Onyinye Ojeh, Kenneth Okoineme, Jane Adizue, Yusuf H. Wada, Elizabeth Adeyemo, Jennifer Anyanti, Abdullahi Musa Yola, A. Umar","doi":"10.3389/ijph.2024.1606807","DOIUrl":"https://doi.org/10.3389/ijph.2024.1606807","url":null,"abstract":"","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"407 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139841553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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