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7. Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Author

Frank, Tahvi D, Carter, Austin, Jahagirdar, Deepa, Biehl, Molly H, Douwes-Schultz, Dirk, Larson, Samantha Leigh, Arora, Megha, Dwyer-Lindgren, Laura, Steuben, Krista M, Abbastabar, Hedayat, Abu-Raddad, Laith Jamal, Abyu, Direslgne Misker, Adabi, Maryam, Adebayo, Oladimeji M, Adekanmbi, Victor, Adetokunboh, Olatunji O, Ahmadi, Alireza, Ahmadi, Keivan, Ahmadian, Elham, Ahmadpour, Ehsan, Ahmed, Muktar Beshir, Akal, Chalachew Genet, Alahdab, Fares, Alam, Noore, Albertson, Samuel B, Alemnew, Birhan Tamene T, Alene, Kefyalew Addis, Alipour, Vahid, Alvis-Guzman, Nelson, Amini, Saeed, Anbari, Zohreh, Anber, Nahla Hamed, Anjomshoa, Mina, Antonio, Carl Abelardo T, Arabloo, Jalal, Aremu, Olatunde, Areri, Habtamu Abera, Asfaw, Ephrem Tsegay, Ashagre, Alebachew Fasil, Asmelash, Daniel, Asrat, Anemaw A, Avokpaho, Euripide F G A, Awasthi, Ashish, Awoke, Nefsu, Ayanore, Martin Amogre, Azari, Samad, Badawi, Alaa, Bagherzadeh, Mojtaba, Banach, Maciej, Barac, Aleksandra, Bärnighausen, Till Winfried, Basu, Sanjay, Bedi, Neeraj, Behzadifar, Masoud, Bekele, Bayu Begashaw, Belay, Saba Abraham, Belay, Yared Belete, Belayneh, Yaschilal Muche, Berhane, Adugnaw, Bhat, Anusha Ganapati, Bhattacharyya, Krittika, Biadgo, Belete, Bijani, Ali, Bin Sayeed, Muhammad Shahdaat, Bitew, Helen, Blinov, Andrew, Bogale, Kassawmar Angaw, Bojia, Hunduma Amensisa, Burugina Nagaraja, Sharath B N, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campuzano Rincon, Julio Cesar, Carvalho, Félix, Chattu, Vijay Kumar, Christopher, Devasahayam J, Chu, Dinh-Toi, Crider, Raquel, Dahiru, Tukur, Dandona, Lalit, Dandona, Rakhi, Daryani, Ahmad, das Neves, José, De Neve, Jan-Walter, Degenhardt, Louisa, Demeke, Feleke Mekonnen, Demis, Asmamaw Bizuneh, Demissie, Dereje Bayissa, Demoz, Gebre Teklemariam, Deribe, Kebede, Des Jarlais, Don, Dhungana, Govinda Prasad, Diaz, Daniel, Djalalinia, Shirin, Do, Huyen Phuc, Doan, Linh Phuong, Duber, Herbert, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duko Adema, Bereket, Effiong, Andem, Eftekhari, Aziz, El Sayed Zaki, Maysaa, El-Jaafary, Shaimaa I, El-Khatib, Ziad, Elsharkawy, Aisha, Endries, Aman Yesuf, Eskandarieh, Sharareh, Eyawo, Oghenowede, Farzadfar, Farshad, Fatima, Batool, Fentahun, Netsanet, Fernandes, Eduarda, Filip, Irina, Fischer, Florian, Folayan, Morenike Oluwatoyin, Foroutan, Masoud, Fukumoto, Takeshi, Fullman, Nancy, Garcia-Basteiro, Alberto L, Gayesa, Reta Tsegaye, Gebremedhin, Ketema Bizuwork, Gebremeskel, Gebreamlak Gebremedhn Gebremedhn, Gebreyohannes, Kelali Kalaye, Gedefaw, Getnet Azeze, Gelaw, Belayneh K, Gesesew, Hailay Abrha, Geta, Birhanu, Gezae, Kebede Embaye, Ghadiri, Keyghobad, Ghashghaee, Ahmad, Ginindza, Themba T G, Gugnani, Harish Chander, Guimarães, Rafael Alves, Haile, Michael Tamene, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamidi, Samer, Handanagic, Senad, Handiso, Demelash Woldeyohannes, Hanfore, Lolemo Kelbiso, Hasanzadeh, Amir, Hassankhani, Hadi, Hassen, Hamid Yimam, Hay, Simon I, Henok, Andualem, Hoang, Chi Linh, Hosgood, H Dean, Hosseinzadeh, Mehdi, Hsairi, Mohamed, Ibitoye, Segun Emmanuel, Idrisov, Bulat, Ikuta, Kevin S, Ilesanmi, Olayinka Stephen, Irvani, Seyed Sina Naghibi, Iwu, Chinwe Juliana, Jacobsen, Kathryn H, James, Spencer L, Jenabi, Ensiyeh, Jha, Ravi Prakash, Jonas, Jost B, Jorjoran Shushtari, Zahra, Kabir, Ali, Kabir, Zubair, Kadel, Rajendra, Kasaeian, Amir, Kassa, Belete, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kayode, Gbenga A, Kebede, Mihiretu M, Kefale, Adane Teshome, Kengne, Andre Pascal, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khalid, Nauman, Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Junaid, Khang, Young-Ho, Khatab, Khaled, Khazaei, Salman, Khoja, Abdullah T, Kiadaliri, Aliasghar A, Kim, Yun Jin, Kisa, Adnan, Kisa, Sezer, Kochhar, Sonali, Komaki, Hamidreza, Koul, Parvaiz A, Koyanagi, Ai, Kuate Defo, Barthelemy, Kumar, G Anil, Kumar, Manasi, Kuupiel, Desmond, Lal, Dharmesh Kumar, Lee, Jane Jean-Hee, Lenjebo, Tsegaye Lolaso, Leshargie, Cheru Tesema, Macarayan, Erlyn Rachelle King, Maddison, Emilie R, Magdy Abd El Razek, Hassan, Magis-Rodriguez, Carlos, Mahasha, Phetole Walter, Majdan, Marek, Majeed, Azeem, Malekzadeh, Reza, Manafi, Navid, Mapoma, Chabila Christopher, Martins-Melo, Francisco Rogerlândio, Masaka, Anthony, Mayenga, Emmanuel Ngassa Laurent, Mehta, Varshil, Meles, Gebrekiros Gebremichael, Meles, Hagazi Gebre, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mena, Alemayehu Toma, Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Meretoja, Tuomo J, Mestrovic, Tomislav, Miller, Ted R, Moazen, Babak, Mohajer, Bahram, Mohamadi-Bolbanabad, Amjad, Mohammad, Karzan Abdulmuhsin, Mohammad, Yousef, Mohammad Darwesh, Aso, Mohammad Gholi Mezerji, Naser, Mohammadi, Moslem, Mohammadibakhsh, Roghayeh, Mohammadoo-Khorasani, Milad, Mohammed, Jemal Abdu, Mohammed, Shafiu, Mohebi, Farnam, Mokdad, Ali H, Moodley, Yoshan, Moossavi, Maryam, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moschos, Marilita M, Mossie, Tilahun Belete, Mousavi, Seyyed Meysam, Muchie, Kindie Fentahun, Muluneh, Atalay Goshu, Muriithi, Moses K, Mustafa, Ghulam, Muthupandian, Saravanan, Nagarajan, Ahamarshan Jayaraman, Naik, Gurudatta, Najafi, Farid, Nazari, Javad, Ndwandwe, Duduzile Edith, Nguyen, Cuong Tat, Nguyen, Huong Lan Thi, Nguyen, Son Hoang, Nguyen, Trang Huyen, Ningrum, Dina Nur Anggraini, Nixon, Molly R, Nnaji, Chukwudi A, Noroozi, Mehdi, Noubiap, Jean Jacques, Nourollahpour Shiadeh, Malihe, Obsa, Mohammed Suleiman, Odame, Emmanuel Ankrah, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olum, Solomon, Oppong Asante, Kwaku Oppong Asante, Oren, Eyal, Otstavnov, Stanislav S, PA, Mahesh, Padubidri, Jagadish Rao, Pakhale, Smita, Pakpour, Amir H, Patel, Sangram Kishor, Paulos, Kebreab, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Piroozi, Bakhtiar, Pourshams, Akram, Qorbani, Mostafa, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Sajjad ur, Ranabhat, Chhabi Lal, Rawaf, Salman, Reis, Cesar, Renjith, Vishnu, Reta, Melese Abate, Rezai, Mohammad Sadegh, Rios González, Carlos Miguel, Roro, Elias Merdassa, Rostami, Ali, Rubino, Salvatore, Saeedi Moghaddam, Sahar, Safari, Saeed, Sagar, Rajesh, Sahraian, Mohammad Ali, Salem, Marwa R Rashad, Salimi, Yahya, Salomon, Joshua A, Sambala, Evanson Zondani, Samy, Abdallah M, Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Sayyah, Mehdi, Schutte, Aletta Elisabeth, Sepanlou, Sadaf G, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shaheen, Amira A, Shaikh, Masood Ali, Shallo, Seifadin Ahmed, Shamsizadeh, Morteza, Sharifi, Hamid, Shibuya, Kenji, Shin, Jae Il, Shirkoohi, Reza, Silva, Diego Augusto Santos, Silveira, Dayane Gabriele Alves, Singh, Jasvinder A, Sisay, Malede Mequanent M, Sisay, Mekonnen, Sisay, Solomon, Smith, Amanda E, Sokhan, Anton, Somayaji, Ranjani, Soshnikov, Sergey, Stein, Dan J, Sufiyan, Mu'awiyyah Babale, Sunguya, Bruno F, Sykes, Bryan L, Tadesse, Birkneh Tilahun, Tadesse, Degena Bahrey, Tamirat, Koku Sisay, Taveira, Nuno, Tekelemedhin, Shishay Wahdey, Temesgen, Habtamu Denekew, Tesfay, Fisaha Haile, Teshale, Manaye Yihune, Thapa, Subash, Tlaye, Kenean Getaneh, Topp, Stephanie M, Tovani-Palone, Marcos Roberto, Tran, Bach Xuan, Tran, Khanh Bao, Ullah, Irfan, Unnikrishnan, Bhaskaran, Uthman, Olalekan A, Veisani, Yousef, Vladimirov, Sergey Konstantinovitch, Wada, Fiseha Wadilo, Waheed, Yasir, Weldegwergs, Kidu Gidey, Weldesamuel, Girmay Teklay T, Westerman, Ronny, Wijeratne, Tissa, Wolde, Haileab Fekadu, Wondafrash, Dawit Zewdu, Wonde, Tewodros Eshete, Wondmagegn, Berhanu Yazew, Yeshanew, Addisu Gize, Yilma, Mekdes Tigistu, Yimer, Ebrahim M, Yonemoto, Naohiro, Yotebieng, Marcel, Youm, Yoosik, Yu, Chuanhua, Zaidi, Zoubida, Zarghi, Afshin, Zenebe, Zerihun Menlkalew, Zewale, Taye Abuhay, Ziapour, Arash, Zodpey, Sanjay, Naghavi, Mohsen, Vollset, Stein Emil, Wang, Haidong, Lim, Stephen S, Kyu, Hmwe Hmwe, and Murray, Christopher J L

Published
2019
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12. The prevalence of metabolic conditions before and during the COVID-19 pandemic and its association with health and sociodemographic factors

Author

Mamudu, Hadii M., primary, Adzrago, David, additional, Odame, Emmanuel O., additional, Dada, Oluwabunmi, additional, Nriagu, Valentine, additional, Paul, Trishita, additional, Weierbach, Florence W., additional, Dowling-McClay, Karilynn, additional, Stewart, David W., additional, Adams, Jessica, additional, and Paul, Timir K., additional

Published
2023
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18. miR-145-3p Inhibits MuSCs Proliferation and Mitochondria Mass via Targeting MYBL1 in Jianzhou Big-Eared Goats.

Author

Odame, Emmanuel, Li, Li, Nabilla, Joshua Abdulai, Cai, He, Xiao, Miao, Ye, Jiangfeng, Chen, Yuan, Kyei, Bismark, Dai, Dinghui, Zhan, Siyuan, Cao, Jiaxue, Guo, Jiazhong, Zhong, Tao, Wang, Linjie, and Zhang, Hongping

Subjects
*MUSCLE regeneration, *CIRCULAR RNA, *MAMMAL development, *MITOCHONDRIA, *GOATS, *CELL physiology, *MUSCLE growth
Abstract

Muscle growth and injury-induced regeneration are controlled by skeletal muscle satellite cells (MuSCs) through myogenesis in postnatal animals. Meanwhile, myogenesis is accompanied by mitochondrial function and enzyme activity. Nevertheless, the underlying molecular mechanisms involving non-coding RNAs including circular RNAs (circRNAs) and microRNAs (miRNAs) remain largely unsolved. Here, we explored the myogenic roles of miR-145-3p and MYBL1 on muscle development and mitochondrial mass. We noticed that overexpression of miR-145-3p inhibited MuSCs proliferation and reduced the number of viable cells. Meanwhile, deficiency of miR-145-3p caused by LNAantimiR-145-3p or an inhibitor retarded the differentiation of MuSCs. miR-145-3p altered the mitochondrial mass in MuSCs. Moreover, miR-145-3p targeted and negatively regulated the expression of CDR1as and MYBL1. The knockdown of the MYBL1 using ASO-2′MOE modification simulated the inhibitory function of miR-145-3p on cell proliferation. Additionally, MYBL1 mediated the regulation of miR-145-3p on Vexin, VCPIP1, COX1, COX2, and Pax7. These imply that CDR1as/miR-145-3p/MYBL1/COX1, COX2, VCPIP1/Vexin expression at least partly results in a reduction in mitochondrial mass and MuSCs proliferation. These novel findings confirm the importance of mitochondrial mass during myogenesis and the boosting of muscle/meat development in mammals. [ABSTRACT FROM AUTHOR]

Published
2023
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20. Disparities in localized malignant lung cancer surgical treatment: A population‐based cancer registry analysis.

Author

Mamudu, Lohuwa, Salmeron, Bonita, Odame, Emmanuel A., Atandoh, Paul H., Reyes, Joanne L., Whiteside, Martin, Yang, Joshua, Mamudu, Hadii M., and Williams, Faustine

Subjects
LUNG cancer, CANCER treatment, LOGISTIC regression analysis, OVERALL survival, ODDS ratio
Abstract

Background: Lung cancer (LC) continues to be the leading cause of cancer deaths in the United States. Surgical treatment has proven to offer a favorable prognosis and a better 5‐year relative survival for patients with early or localized tumors. This novel study investigates the factors associated with the odds of receiving surgical treatment for localized malignant LC in Tennessee. Methods: Population‐based data of 9679 localized malignant LC patients from the Tennessee Cancer Registry (2005–2015) were utilized to examine the factors associated with receiving surgical treatment for localized malignant LC. Bivariate and multivariate logistic regression analyses, cross‐tabulation, and Chi‐Square (χ2) tests were conducted to assess these factors. Results: Patients with localized malignant LC who initiated treatment after 2.7 weeks were 46% less likely to receive surgery (adjusted odds ratio [AOR] = 0.54; 95% confidence interval [CI] = 0.50–0.59; p < 0.0001). Females had a greater likelihood (AOR = 1.14; CI = 1.03–1.24) of receiving surgical treatment compared to men. Blacks had lower odds (AOR = 0.76; CI = 0.65–0.98) of receiving surgical treatment compared to Whites. All marital groups had higher odds of receiving surgical treatment compared to those who were single/never married. Patients living in Appalachian county had lower odds of receiving surgical treatment (AOR = 0.65; CI = 0.59–0.71) compared with those in the non‐Appalachian county. Patients with private (AOR = 2.09; CI = 1.55–2.820) or public (AOR = 1.42; CI = 1.06–1.91) insurance coverage were more likely to receive surgical treatment compared to self‐pay/uninsured patients. Overall, the likelihood of patients receiving surgical treatment for localized malignant LC decreases with age. Conclusion: Disparities exist in the receipt of surgical treatment among patients with localized malignant LC in Tennessee. Health policies should target reducing these disparities to improve the survival of these patients. [ABSTRACT FROM AUTHOR]

Published
2023
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21. Knockdown of CDR1as Decreases Differentiation of Goat Skeletal Muscle Satellite Cells via Upregulating miR-27a-3p to Inhibit ANGPT1

Author

Kyei, Bismark, primary, Odame, Emmanuel, additional, Li, Li, additional, Yang, Liu, additional, Zhan, Siyuan, additional, Li, Juntao, additional, Chen, Yuan, additional, Dai, Dinghui, additional, Cao, Jiaxue, additional, Guo, Jiazhong, additional, Zhong, Tao, additional, Wang, Linjie, additional, and Zhang, Hongping, additional

Published
2022
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23. Additional file 1 of Supporting a review of the benefits package of the National Health Insurance Scheme in Ghana

Author

Vellekoop, Heleen, Odame, Emmanuel, and Ochalek, Jessica

Abstract

Additional file 1. S1. Details of literature search on DALYs avoided. S2. References of cost-effectiveness studies included. S3. Data sources used to calculate annual population in need. S4. Calculating the annual budget available for claims reimbursement. S5. Calculating reduced healthcare demand. S6. Details on the sensitivity analysis. S7. Calculating the budget impact of implementing all interventions under consideration. S8. Co-payments for interventions in coinsurance packages. S9. Outcome tables for the sensitivity analysis.

Published
2022
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27. Overview of preparedness and response to COVID-19 in Ghana

Author

Sarkodie, Badu, primary, Asiedu-Bekoe, Franklin, additional, O. Laryea, Dennis, additional, K. Ampofo, William, additional, O. Phillips, Richard, additional, Samba, Ali, additional, Aboagye, Da Costa, additional, Nsiah-Asare, Anthony, additional, Asamoah-Baah, Anarfi, additional, Odame, Emmanuel, additional, Ohene, Sally-Anne, additional, A. Amoako, Yaw, additional, and Kuma-Aboagye, Patrick, additional

Published
2021
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29. CircRNA—Protein Interactions in Muscle Development and Diseases

Author

Zheng, Shuailong, primary, Zhang, Xujia, additional, Odame, Emmanuel, additional, Xu, Xiaoli, additional, Chen, Yuan, additional, Ye, Jiangfeng, additional, Zhou, Helin, additional, Dai, Dinghui, additional, Kyei, Bismark, additional, Zhan, Siyuan, additional, Cao, Jiaxue, additional, Guo, Jiazhong, additional, Zhong, Tao, additional, Wang, Linjie, additional, Li, Li, additional, and Zhang, Hongping, additional

Published
2021
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32. Between and Within Sexual Identity-Group Differences in Asthma Prevalence in the United States.

Author

Adzrago, David, Nyarko, Samuel H., Ananaba, Nnenna, Asare, Matt, Odame, Emmanuel, Jones, Antwan, Paul, Timir K., and Mamudu, Hadii M.

Subjects
ASTHMA risk factors, OBESITY complications, STATISTICS, MINORITIES, ASTHMA, CONFIDENCE intervals, CROSS-sectional method, SELF-evaluation, MULTIVARIATE analysis, RISK assessment, COMPARATIVE studies, SEXUAL orientation identity, DESCRIPTIVE statistics, CHI-squared test, STATISTICAL hypothesis testing, ETHNIC groups, SMOKING, STATISTICAL sampling, BODY mass index, SOCIODEMOGRAPHIC factors, LOGISTIC regression analysis, ODDS ratio, DATA analysis software, SECONDARY analysis
Abstract

BACKGROUND: Although prior studies have established the association of asthma with smoking and obesity, literature on difference-in-differences analyses involving sexual identity is sparse. Therefore, this study aimed to examine the between and within sexual identity-group differences in asthma prevalence among individuals who smoke and are obese. METHODS: We aggregated the 2017-2019 National Survey on Drug Use and Health data on adults (N = 128,319) to perform weighted multivariable logistic regression analysis and marginal estimates and marginsplot to determine asthma prevalence by sexual identity and the status of smoking and obesity. RESULTS: About 66% of the study population reported having asthma. Among the individuals with asthma, 42% were obese, 10% were daily cigarette smokers, and 6% identified as bisexual persons. Lesbian/gay daily smokers (86%) or former smokers (75%) had a higher probability of having asthma than bisexual (daily smokers = 78% vs former smokers = 72%) and heterosexual (daily smokers = 68% vs former smokers = 65%) persons. Within each sexual identity subgroup, daily smokers (68-86%) had the highest probability of asthma. Obese bisexual (73%) or lesbian/gay (72%) persons had higher probabilities of having asthma than heterosexual persons (69%). Obese (73%) or overweight (72%) bisexual (compared to normal weight = 70% or underweight = 51%) and obese (69%) or overweight (65%) heterosexual (compared to normal weight = 62% or underweight = 57%) persons had the highest probabilities of having asthma within their groups, whereas overweight persons (overweight = 81% vs underweight = 79%, normal weight = 78%, and obese = 72%) had the highest probabilities within lesbian/gay persons. CONCLUSIONS: Smoking and obesity show heightened odds for asthma, with significant odds for sexual minorities in asthma diagnosis relative to heterosexuals. These findings provide formative information for future longitudinal and experimental studies to explore these mechanisms of asthma risks among sexual and gender minorities. [ABSTRACT FROM AUTHOR]

Published
2022
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34. CDR1as related miRNA-mRNA networks in differentiating goat skeletal muscle satellite cells

Author

Kyei, Bismark, primary, Li, Li, additional, Yang, Liu, additional, Zhan, Siyuan, additional, Li, Juntao, additional, Chen, Yuan, additional, Zhang, Xujia, additional, Zheng, Shuailong, additional, Xu, Xiaoli, additional, Odame, Emmanuel, additional, Cao, Jiaxue, additional, Guo, Jiazhong, additional, Zhong, Tao, additional, Wang, Linjie, additional, and Zhang, Hongping, additional

Published
2020
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39. A systematic review of Health Technology Assessment tools in sub-Saharan Africa: methodological issues and implications

Author

Kriza, Christine, Hanass-Hancock, Jill, Odame, Emmanuel Ankrah, Deghaye, Nicola, Aman, Rashid, Wahlster, Philip, Marin, Mayra, Gebe, Nicodemus, Akhwale, Willis, Wachsmuth, Isabelle, and Kolominsky-Rabas, Peter L.

Subjects
Health Services Needs and Demand, Evidence-Based Medicine, Technology Assessment, Biomedical, ddc:916, Cost-Benefit Analysis, Health Policy, Review, Health systems research, Health services, Decision Support Techniques, Resource Allocation, Health systems, Medizinische Fakultät, Humans, ddc:610, Health Services Research, Poverty, Africa South of the Sahara
Abstract

Background Health technology assessment (HTA) is mostly used in the context of high- and middle-income countries. Many “resource-poor” settings, which have the greatest need for critical assessment of health technology, have a limited basis for making evidence-based choices. This can lead to inappropriate use of technologies, a problem that could be addressed by HTA that enables the efficient use of resources, which is especially crucial in such settings. There is a lack of clarity about which HTA tools should be used in these settings. This research aims to provide an overview of proposed HTA tools for “resource-poor” settings with a specific focus on sub-Saharan Africa (SSA). Methodology A systematic review was conducted using basic steps from the PRISMA guidelines. Studies that described HTA tools applicable for “resource-limited” settings were identified and critically appraised. Only papers published between 2003 and 2013 were included. The identified tools were assessed according to a checklist with methodological criteria. Results Six appropriate tools that are applicable in the SSA setting and cover methodological robustness and ease of use were included in the review. Several tools fulfil these criteria, such as the KNOW ESSENTIALS tool, Mini-HTA tool, and Multi-Criteria Decision Analysis but their application in the SSA context remains limited. The WHO CHOICE method is a standardized decision making tool for choosing interventions but is limited to their cost-effectiveness. Most evaluation of health technology in SSA focuses on priority setting. There is a lack of HTA tools that can be used for the systematic assessment of technology in the SSA context. Conclusions An appropriate HTA tool for “resource-constrained” settings, and especially SSA, should address all important criteria of decision making. By combining the two most promising tools, KNOW ESSENTIALS and Multi-Criteria Decision Analysis, appropriate analysis of evidence with a robust and flexible methodology could be applied for the SSA setting.

Published
2014

40. Reliability of Wearable Technology to Monitor Core Temperature Among Helicopter-Based EMS Crews

Author

Callihan, Michael, Cole, Heather, Callihan, Amanda, Penn, Elizabeth, Peek, Lauren, Barrow, Mahalia, Lungu, Claudiu, Odame, Emmanuel Atuahene, Oh, Jonghwa, Stokley, Holly, Wickliffe, Jeffrey, and Winchester, Lee

Abstract

Background: Excessive heat stress led to more than 400 deaths in the United States from 2011 to 2021. Common methods for heat injury prevention revolve around measurements of the environment and fail to account for the unique individual response to stressors.Methods: An observational approach was utilized with nine helicopter-based emergency medical services personnel during emergency flights to compare core temperature readings obtained from an ingestible temperature monitoring pill and the estimated core temperature reading of the Slate Safety Band V2 wearable device. Comparison of data was conducted within Microsoft Excel programming to determine the mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), mean biased error (MBE), and Bland–Altman plot development.Findings: A significant bias (t= 17.58, p< .001) toward the Slate Safety device reading higher with an average difference of −0.48°C (−0.86°F) was found, meaning the average temperature reading is 0.48°C (−0.86°F) higher with the Slate Safety device. A significant correlation of .26 (p< .001) was noted between the ingestible pill and the wearable device with a 95% confidence interval of 0.23 to 0.29. Aggregate core temperature data demonstrated an MSE of 0.43, an RMSE of 0.65, an MAE of 0.54, and an MBE of −0.48.Conclusions/Application to Practice: The ability to monitor the physiological parameters of a worker remotely adds safety tools relative to the risks of heat stress. The slightly higher reading associated with the Slate Safety wearable device provides an added safety margin to protect our workers.

Published
2024
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43. Systematic Review of Economic Evaluation Literature in Ghana: Is Health Technology Assessment the Future?

Author

Odame, Emmanuel Ankrah

Abstract

Abstract: Objectives: In many countries, such as Ghana, there is an increasing impetus to use economic evaluation to allow more explicit and transparent health care priority setting. An important question for policymakers in low-income countries, however, is whether it is possible to introduce economic evaluation data into health care priority-setting decisions. Methods: This article systematically reviewed the literature on economic evaluation on medical devices and pharmaceuticals in Ghana published between 1997 and 2012. Its aim was to analyze the quantity, quality, and targeting of economic evaluation studies that relate to medical devices and pharmaceuticals and provide a framework for those conducting similar health technology assessment reviews in similar contexts. Results: The review revealed that the number of publications reporting economic evaluations was minimal with regard to medical devices and pharmaceuticals. Conclusions: With the introduction of the National Health Insurance Scheme since 2004 policymakers are confronted with the challenge of allocating scarce resources rationally. Priority setting therefore has to be guided by a sound knowledge of the costs of providing health services. The need for economic evaluation is thus important. More costing studies were found; there were very few cost-effectiveness analysis studies. If economic evaluation is useful for policymakers only when performed correctly and reported accurately, these findings depict barriers to using economic evaluation to assist decision-making processes in Ghana; hence, there is a need for an independent health technology assessment unit. [Copyright &y& Elsevier]

Published
2013
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