Dynamic Panel Surveillance of COVID-19 Transmission in the United States to Inform Health Policy: Observational Statistical Study – A Critical Review of Article

Download Article

DOI: 10.21522/TIJPH.2013.09.04.Art009

Authors : N.P. Sithole Sibanda, E. Sibanda, N. Ndlovu, C. Sibanda


This is a critical appraisal of a manuscript outlining additional indicators used in the United States to augment traditional disease surveillance tools. The article went through the peer-review process. Therefore, it may be considered as objective and unbiased. The structure of the article is coherent, and it was published in a journal for digital medicine, health, and health care in the internet age. The article has contributed to the literature and provides a basis for strengthening existing surveillance systems to improve public health outcomes. However, it is suggested that whenever new indicators are being developed, their essential components must be fully defined.

Keywords: Covid-19, Surveillance, United States.


[1]   Oehmeke, J.F, Moss, C.B, Singh, L.N, Oehmeke, T.B, Post, LA. (2020). ‘Dynamic Panel Surveillance of COVID-19 Transmission I, the United States, to Inform Health Policy: Observational Statistical Study’, Journal of Medical Internet Research. http://dx.doi.org/10.5772/intechopen.79794.

[2]   WHO (2020). COVID-19 Strategic Preparedness and Response Plan Operational Planning Guidelines to Support Country Preparedness and Response. https://www.who.int/docs/default-source/coronaviruse/covid-19-sprp-unct-guidelines.pdf?sfvrsn=81ff43d8_4.

[3] Zimbabwe Ministry of Health and Child Care. (2020). COVID-19 Pillars. Retrieved from http://www.mohcc.gov.zw/index.phpoption=com_phocadownload&view=category&id=16&Itemid=746.

[4]   Post, L., Marogi, E., Moss, C. B., Murphy, R. L., Ison, M. G., Achenbach, C. J., Resnick, D., Singh, L., White, J., Boctor, M. J., Welch, S. B., & Oehmke, J. F. (2021). SARS-CoV-2 Surveillance in the Middle East and North Africa: Longitudinal Trend Analysis. Journal of Medical Internet Research, 23(1), e25830. https://doi.org/10.2196/25830.

[5] Eysenbach, G. & Kukafka, R. (2020). Advancing Digital Health and Open Science. Journal of Medical Internet Research Publications. JMIR, ISSN 1438-8871 https://www.jmir.org.

[6] Rampal, L., Liew, B. S., Choolani, M., Ganasegeran, K., Pramanick, A., Vallibhakara, S. A., Tejativaddhana, P., & Hoe, V. C. (2020). Battling COVID-19 pandemic waves in six South-East Asian countries: A real-time consensus review. The Medical journal of Malaysia, 75(6), 613–625.

[7] Guest, G., & Namey, E. (2017). Public health research methods. SAGE Publications, Inc. https://www.doi.org/10.4135/9781483398839.

[8] World Health Organisation. (2003). STEPS: A Framework for Surveillance. The WHO Stepwise approach to Surveillance of Non-communicable Diseases (STEPS).


[9]   Klaucke, D.N., Buehler, J.W., Thacker, S.T. et al. (1988). Guidelines for Evaluating Surveillance Systems. BMC Center for Disease Control (CDC). https://www.cdc.gov/mmwr/preview/mmwrhtml/00001769.htm.

[10]  Shanbehzadeh M, Kazemi-Arpanahi H, Mazhab-Jafari K, Haghiri H. (2020). Coronavirus disease 2019 (COVID-19) surveillance system: Development of COVID-19 minimum data set and interoperable reporting framework. J Edu Health Promot; 9:203.

[11]  Post, L. A., Benishay, E. T., Moss, C. B., Murphy, R. L., Achenbach, C. J., Ison, M. G., Resnick, D., Singh, L. N., White, J., Chaudhury, A. S., Boctor, M. J., Welch, S. B., & Oehmke, J. F. (2021). Surveillance Metrics of SARS-CoV-2 Transmission in Central Asia: Longitudinal Trend Analysis. Journal of Medical Internet Research, 23(2), e25799. https://doi.org/10.2196/25799.

[12] Hayakawa, Kazuhiko. (2009). First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models: A Simulation Study. Economics Bulletin. 29. 2008-2017.

[13] Ytsunomiya, YT, Utsunomiya, ATH, Torrecilha, FBP, Paulan, S C, Milanesi, M, Garcia, JF. (2020). Growth Rate and Acceleration Analysis of the COVID-19 Pandemic Reveals the Effect of Public Health Measures in Real Time. https://doi.org/10.3389/fmed.2020.00247.

[14] Alexander, M. 1996. Performance Monitoring Indicators: A handbook for Task Managers. World Bank Operations Policy Department, Washington D.C.

[15]  UN Women (2010). Indicators: Virtual Knowledge Centre to End Violence Against Women and Girls.


[16] Hales, D. (2009). An Introduction to Indicators: UNAIDS Monitoring and Evaluation Fundamentals. Joint United Nations Program on HIV/AIDS. Geneva 27, Switzerland. Retrieved from https://www.unaids.org/sites/default/files/sub_landing/files/8_2-Intro-to-IndicatorsFMEF.pdf

[17] Brañas-Garza, P, Bucheli, M & Garcia-Muñoz, T. (2011). Dynamic panel data: A useful technique in experiments, The Papers 10/22, Department of Economic Theory and Economic History of the University of Granada. http://www.fao.org/3/a-i5188e.pdf.

[18] Baum, C.F. (2013). Dynamic Panel Data Estimators [PowerPoint slides]. Applied Econometrics, Boston College. http://fmwww.bc.edu/ecc/s2013/823/EC823.S2013.nn05.slides.pdf.

[19] Clower, E. (2021). Introduction to the Fundamentals of Panel Data. Aptech Systems, Inc https://www.aptech.com/ Volume 35, Issue 8, pages 1084–1109, https://doi.org/10.1093/heapol/czaa03.

[20]  Hayakawa, K. (2009). First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models: A Simulation Study. Economics Bulletin, Access Econ, vol. 29(3), pages 2008-2017. https://ideas.repec.org/a/ebl/ecbull/eb-09-00361.html.

[21] Richards CL, Iademarco MF, Atkinson D, Pinner RW, Yoon P, Mac Kenzie WR, et al. (2017). Advances in Public Health surveillance and information dissemination at the centers for disease control and Prevention. Public Health Rep; 132:403‑10.