Asia Pacific Journal of Health Management http://journal.achsm.org.au/index.php/achsm <p>The Asia Pacific Journal of Health Management (APJHM) is a peer-reviewed journal for managers of organisations offering healthcare and aged care services. The APJHM aims to promote the discipline of health management throughout the region by facilitating the transfer of knowledge among readers by widening the evidence base for management practices.<br /><br />*Print 1(1);2006 - 5(1);2010 Online 4(2);2009 - current<br />*ISSN 2204-3136 (online); ISSN 1833-3818 (print) </p> en-US yaping.liu@achsm.org.au (Yaping Liu) journal@achsm.org.au (Yaping Liu) Wed, 25 Nov 2020 17:37:12 -0800 OJS 3.2.1.1 http://blogs.law.harvard.edu/tech/rss 60 Investigating the cases of novel coronavirus disease (COVID-19) in Tunisia using dynamic statistical techniques http://journal.achsm.org.au/index.php/achsm/article/view/703 <p>The pandemic of Covid-19 has been spreading in Tunisia officially since March 2, 2020. All 24 governorates of Tunisia are gradually affected. The novel coronavirus disease (COVID-19) evaluation with new estimation approaches has gained significant interest from several researchers. This work aims to develop a time series in the Tunisian context to build conceptual tools that explore the association between death from COVID-19 and confirmed cases. We collected daily data on two health indicators: confirmed cases and deaths in 24 governorates in Tunisia. Because of the ambiguity of COVID-19, we investigated unobserved factors, including environmental exposures, which explain the spread of the disease through human-to-human transmission. Also, we used specific estimation methods to control cross-sectional dependence, endogeneity, and unobserved heterogeneity. We have found that increase in confirmed cases by 1% could increase the death from coronavirus by 0.035%, while the log death seems to have the highest impact rate with over 0.96% increase in death from coronavirus. We also confirmed the presence of unobserved heterogeneity and common factors that facilitates the novel coronavirus attributable deaths caused by increased levels of confirmed cases.</p> Abdulrasheed Zakari Copyright (c) http://journal.achsm.org.au/index.php/achsm/article/view/703 Investigating the cases of novel coronavirus disease (COVID-19) in Tunisia using dynamic statistical techniques http://journal.achsm.org.au/index.php/achsm/article/view/701 <p>The pandemic of Covid-19 has been spreading in Tunisia officially since March 2, 2020. All 24 governorates of Tunisia are gradually affected especially during this month. Indeed, the novel coronavirus disease (COVID-19) evaluation with new estimation approaches has gained significant interest from several researchers. This work aims to develop a time series in the Tunisian context to build conceptual tools that explore the association between death from COVID-19 and confirmed cases. We collected daily data on two health indicators: confirmed cases and deaths in 24 governorates in Tunisia. Because of the ambiguity of COVID-19, we investigated unobserved factors, including environmental exposures, which explain the spread of the disease through human-to-human transmission. Also, we used specific estimation methods to control cross-sectional dependence, endogeneity, and unobserved heterogeneity. We have found that increase in confirmed cases by 1% could increase the death from coronavirus by 0.035%, while the log death seems to have the highest impact rate with over 0.96% increase in death from coronavirus. We also confirmed the presence of unobserved heterogeneity and common factors that facilitates the novel coronavirus attributable deaths caused by increased levels of confirmed cases.</p> Abdulrasheed Zakari Copyright (c) http://journal.achsm.org.au/index.php/achsm/article/view/701