COVID-19 mortality in the Philippines: province-level ecological analysis, 2020-2023.

IF 1.6 Q4 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Western Pacific Surveillance and Response Pub Date : 2026-03-25 eCollection Date: 2026-01-01 DOI:10.5365/wpsar.2026.17.1.1128
Jimuel Celeste, Jesus Emmanuel Sevilleja, Vena Pearl Bongolan, Roselle Leah Rivera, Salvador Eugenio Caoili, Romulo de Castro
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引用次数: 0

Abstract

Objective: To investigate COVID-19 mortality in Philippine provinces from 2020 to 2023.

Methods: Crude mortality rate (CMR), age-standardized mortality rate (ASMR) and age-specific mortality rate were computed for 84 areas (82 provinces and 2 cities) using COVID-19 surveillance data from the Philippine Department of Health, which captured data about confirmed deaths occurring between 20 January 2020 and 9 May 2023. Provinces were ranked by their ASMR. A correlation analysis was conducted to identify possible predictors of COVID-19 mortality. Among the factors investigated were the incidence of poverty, population density, proportion of the population considered elderly (aged ≥ 65 years), hospital bed density and COVID-19 testing rates.

Results: Eight of the 10 provinces that had the highest COVID-19 ASMRs were located in the Luzon island group. The province with the highest ASMR was Benguet in Northern Luzon (207.83 deaths/100 000 population), and the lowest rate was in Tawi-Tawi in Southwestern Mindanao (2.22 deaths/100 000 population). The incidence of poverty was negatively correlated with COVID-19 mortality, while hospital bed density and COVID-19 testing rates were positively correlated with CMRs and ASMRs.

Discussion: This analysis provides a starting point for investigating COVID-19 mortality in Philippine provinces. The ranking of provinces by their ASMR is useful for directing future epidemiological investigations and, coupled with the results of the correlation analysis, provides insight into the factors that may have impacted COVID-19 mortality in the Philippines. Our analysis suggests that COVID-19 mortality patterns can partly be explained by the streetlight effect and factors linked to the availability of and access to health care.

菲律宾2019冠状病毒病死率:2020-2023年省级生态分析
目的:调查2020 - 2023年菲律宾各省COVID-19死亡率。方法:利用菲律宾卫生部收集的2020年1月20日至2023年5月9日期间发生的确诊死亡数据,计算84个地区(82个省和2个城市)的粗死亡率(CMR)、年龄标准化死亡率(ASMR)和年龄特异性死亡率。各省按其ASMR进行排名。进行了相关分析,以确定COVID-19死亡率的可能预测因素。调查的因素包括贫困率、人口密度、老年人口比例(≥65岁)、医院床位密度和COVID-19检测率。结果:新冠肺炎asmr最高的10个省份中有8个位于吕宋岛群。ASMR最高的省份是吕宋岛北部的本盖特省(207.83例/10万人口),最低的是棉兰老岛西南部的塔威-塔威省(2.22例/10万人口)。贫困发生率与COVID-19死亡率呈负相关,医院床位密度和COVID-19检测率与cmr和asmr呈正相关。讨论:该分析为调查菲律宾各省COVID-19死亡率提供了一个起点。按ASMR对各省进行排名有助于指导未来的流行病学调查,并与相关分析结果相结合,有助于深入了解可能影响菲律宾COVID-19死亡率的因素。我们的分析表明,COVID-19的死亡率模式可以部分解释为路灯效应以及与医疗保健的可获得性和可获得性相关的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Western Pacific Surveillance and Response
Western Pacific Surveillance and Response PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
1.70
自引率
0.00%
发文量
23
审稿时长
15 weeks
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