The Impact of World Pandemics on Health Services Management: The Covid 19 Experience in Nigeria and Australia

This research aims to evaluate the impact of COVID-19 pandemic on health services management using the COVID-19 experiences as the major means of measure. Secondary data would be used to compare the Low and Medium-Income Countries (LMIC) and the High-Income Countries (HIC), focusing on health systems in Nigeria as a LMIC and Australia as a HIC. The research will also develop and operationalise the concept of health care workers’ experiences during pandemics and investigate how the Covid-19 pandemic affected the health workplace, including its long- and short-term impact on HCWs health and wellbeing. This is with a view to exploring the key issues to this phenomenon and developing a theoretical framework for development of future service management intervention policies and strategies in the increasingly volatile health-care climate and workplace.

A conceptual framework has been developed for this study to manage the research process. The direct and indirect impacts provide a summary of the global impacts of the COVID-19 on health services management. As depicted in the figure below,

 

Study design: This was designed to be a comparative observation study and employing secondary data. Mixed methods statistical design would be as outlined (Table 1).

Table 1: Summary of research objectives and data sources.

A	B	C	D	E
Research objective	Potential Sources	Variables	Qual or Quant	Analytic Techniques
1 & 2	(Our World in Data, 2024)	Location, stringency index, deaths	Quantitative	Panel data analysis
(OECD, 2023)	Socioeconomic factors (SEC)	Quantitative	Time series data analysis
WHO Global Health Observatory††	Quantitative	Cross sectional analysis
1 & 3	AIHW‡‡	Health system responses,	Qualitative and Quantitative	Critical Descriptive Analysis and panel data analysis
NCDC*†	Health system response,	Qualitative and quantitative	Thematic Content Analysis
2 & 3	WHO COVID-19 Dashboard*‡	Location, population, deaths, vaccines	Quantitative	Cross sectional analysis
Oxford COVID-19 Government Response Tracker*††	Government response indicator, location, risk	Quantitative and Qualitative	Panel data analysis and Thematic content analysis
All 1 – 3	Literature review		Systematic review	Thematic and meta-analysis

Keys

SEC: Gender, Marital Status, Education Level, Location, Experience, Income, Age, Role

^†https://ourworldindata.org/explorers/coronavirus-data-explorer – re: (Our World in Data, 2024)

^‡Health Workforce - OECD – re: (OECD, 2023)

^††Global Health Workforce statistics database (who.int) – re: (World Health Organization, 2023, 2024a, 2024b)

^‡‡https://www.aihw.gov.au/reports/workforce/health-workforce#impact – re: (AIHW, 2022)

*^†https://ncdc.gov.ng/diseases/sitreps/?cat=14&name=An%20update%20of%20COVID-19%20outbreak%20in%20Nigeria – re: (NCDC, 2023)

*^‡https://data.who.int/dashboards/covid19/cases?n=c – re: (WHO, 2024)

*^††COVID-19 Government Response Tracker | Blavatnik School of Government (ox.ac.uk) – re: (Blavatnik School of Government, 2023)

Setting and data: Secondary data of observational reports would be obtained from World Health Organization (WHO), our world in data, and WHO observatory as well as Australia Institute of Health and Welfare (AIHW) and Nigeria Centre for Disease Control (NCDC). The applications of different data to answer the various research objectives are as indicated (Table 1).

Ethical consideration: In this study, we will utilize secondary data from the World Health Organization (WHO) data dashboard, OECD, Our world in data and the Australian Institute of Health and welfare (AIHW). Thus, this study does not require approval from the Ethics Committee of the University of Southern Queensland, Australia.

The process – graphical illustrations

This study will help elucidate why Australia spent more in COVID-19 pandemic management compared to Nigeria, but also appears to have recorded more casualties. It is hoped that the findings would highlight lesson for HIC and LMIC to learn from each other.   

AIHW. (2022). Health workforce . Retrieved 5th June, 2024 from https://www.aihw.gov.au/reports/workforce/health-workforce#impact

Blavatnik School of Government. (2023). Covid-19 Government Response Tracker .

Retrieved 5th June, 2024 fromhttps://www.bsg.ox.ac.uk/research/covid-19-government-response-trackerr

NCDC. (2023). An update of COVID-19 outbreak in Nigeria . Retrieved 5th June, 2024 from https://ncdc.gov.ng/diseases/sitreps/?cat=14&name=An%20update%20of%20COVID-19%20outbreak%20in%20Nigeria

OECD. (2023). Health Workforce. In Health at a Glance 2023 - OECD Indicators . https://www.oecd.org/health/health-at-a-glance//

Our World in Data. (2024). Estimated cumulative excess deaths per 100,000 people during COVID-19 .

Retrieved 5th June 2024 fromhttps://ourworldindata.org/explorers/coronavirus-data-explorerr

WHO. (2024). WHO COVID-19 dashboard . Retrieved 5th June, 2024 from https://data.who.int/dashboards/covid19/cases?n=c

World Health Organization. (2023). World health statistics 2023: monitoring health for the SDGs, sustainable development goals . Retrieved 5th June 2024 from https://www.who.int/publications/i/item/9789240074323

World Health Organization. (2024a). Global Health Workforce statistics database .

Retrieved 5 June, 2024 fromhttps://www.who.int/data/gho/data/themes/topics/health-workforcee

World Health Organization. (2024b). World health statistics 2023: monitoring health for the SDGs, sustainable development goals . https://iris.who.int/bitstream/handle/10665/376869/9789240094703-eng.pdf?sequence=11