Local government responses for COVID-19 management in the Philippines

被引:21
|
作者
S. Talabis, Dylan Antonio [1 ,2 ]
Babierra, Ariel L. [1 ,2 ]
H. Buhat, Christian Alvin [1 ,2 ]
Lutero, Destiny S. [1 ,2 ]
Quindala, Kemuel M., III [1 ,2 ]
Rabajante, Jomar F. [1 ,2 ,3 ]
机构
[1] Univ Philippines Los Banos, Inst Math Sci & Phys, Laguna, Philippines
[2] Univ Philippines, Resilience Inst, Quezon City, Philippines
[3] Open Univ, Univ Philippines, Fac Educ, Laguna, Philippines
关键词
COVID-19; Local government; Policies; Outlier; Quantitative methods;
D O I
10.1186/s12889-021-11746-0
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Responses of subnational government units are crucial in the containment of the spread of pathogens in a country. To mitigate the impact of the COVID-19 pandemic, the Philippine national government through its Inter-Agency Task Force on Emerging Infectious Diseases outlined different quarantine measures wherein each level has a corresponding degree of rigidity from keeping only the essential businesses open to allowing all establishments to operate at a certain capacity. Other measures also involve prohibiting individuals at a certain age bracket from going outside of their homes. The local government units (LGUs)-municipalities and provinces-can adopt any of these measures depending on the extent of the pandemic in their locality. The purpose is to keep the number of infections and mortality at bay while minimizing the economic impact of the pandemic. Some LGUs have demonstrated a remarkable response to the COVID-19 pandemic. The purpose of this study is to identify notable non-pharmaceutical interventions of these outlying LGUs in the country using quantitative methods. Methods Data were taken from public databases such as Philippine Department of Health, Philippine Statistics Authority Census, and Google Community Mobility Reports. These are normalized using Z-transform. For each locality, infection and mortality data (dataset Y) were compared to the economic, health, and demographic data (dataset X) using Euclidean metric d=(x-y)(2), where x is an element of X and y is an element of Y. If a data pair (x,y) exceeds, by two standard deviations, the mean of the Euclidean metric values between the sets X and Y, the pair is assumed to be a 'good' outlier. Results Our results showed that cluster of cities and provinces in Central Luzon (Region III), CALABARZON (Region IV-A), the National Capital Region (NCR), and Central Visayas (Region VII) are the 'good' outliers with respect to factors such as working population, population density, ICU beds, doctors on quarantine, number of frontliners and gross regional domestic product. Among metropolitan cities, Davao was a 'good' outlier with respect to demographic factors. Conclusions Strict border control, early implementation of lockdowns, establishment of quarantine facilities, effective communication to the public, and monitoring efforts were the defining factors that helped these LGUs curtail the harm that was brought by the pandemic. If these policies are to be standardized, it would help any country's preparedness for future health emergencies.
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页数:15
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