Cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), have been increasing since the virus emerged in Wuhan, China, in December 2019. As of 13 March 2021, confirmed COVID-19 cases have exceeded 119 million infected individuals across 188 countries, with more than 2.6 million recorded deaths.1 National health systems have attempted to contain the pandemic through control measures such as community quarantine and isolation. In the Philippines, an enhanced community quarantine (ECQ) took effect on 15 March 2020 in an effort to flatten the epidemic curve.2 ECQ involves placing stringent limitations on people’s mobility and strict regulations on various industry operations, all of which are enforced by uniformed personnel.3 In spite of the ECQ, active infections have been steadily increasing in the country, at 611 618 total cases and 12 694 deaths as of 13 March 2021.1

We describe three waves of COVID-19 infections in Manila. First, imported cases among Chinese nationals; second, infections amongst Filipinos residing in less densely populated areas; and third, infections amongst Filipinos residing in high-density areas. We highlight this using admissions data from the National Infectious Diseases hospital in Manila.

BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively. CONCLUSION Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.
Cardiovascular Diseases/mortality* ; Cause of Death ; Climate Change/mortality* ; Cold Temperature/adverse effects* ; Hot Temperature/adverse effects* ; Humans ; Japan/epidemiology* ; Mortality/trends* ; Regression Analysis ; Respiratory Tract Diseases/mortality* ; Seasons ; Time