Pandemic inequity in a megacity: a multilevel analysis of individual, community, and health care vulnerability risks for COVID-19 mortality in Jakarta, Indonesia (preprint)

Background The 33 recognized megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and health care factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning March 2, 2020, to August 31, 2021. Methods This retrospective cohort included all residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data, and disease prevalence from Jakarta Health Office surveillance records, and collected sub-district level socio-demographics data from various official sources. We used multi-level logistic regression to examine individual, community and sub-district-level health care factors and their associations with COVID-19-mortality. Findings Of 705,503 cases with a definitive outcome by August 31, 2021, 694,706 (98.5%) recovered and 10,797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93,459) were <18 years, and 51.6% were female. The sub-district level accounted for 1.5% of variance in mortality (p<0.0001). Individual-level factors associated with death were older age, male sex, comorbidities, and, during the first wave, age <5 years (adjusted odds ratio (aOR) 1.56, 95%CI 1.04-2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95%CI 1.17-1.55; reference: wealthiest quarter), high population density (aOR for the highest density 1.34, 95%CI 1.14-2.58; reference: the lowest), low vaccine coverage (aOR for the lowest coverage 1.25, 95%CI 1.13-1.38; reference: the highest). Interpretation In addition to individual risk factors, living in areas with high poverty and density, and low health care performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.

Non-pharmaceutical interventions, vaccination and the Delta variant: epidemiological insights from modelling England's COVID-19 roadmap out of lockdown (preprint)

BackgroundEnglands COVID-19 "roadmap out of lockdown" set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued. Here we assess the roadmap, the impact of the Delta variant, and potential future epidemic trajectories. MethodsWe extended a model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the Delta variant. We calibrated the model to English surveillance data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. FindingsThe roadmap was successful in offsetting the increased transmission resulting from lifting NPIs with increasing population immunity through vaccination. However due to the emergence of Delta, with an estimated transmission advantage of 73% (95%CrI: 68-79) over Alpha, fully lifting NPIs on 21 June 2021 as originally planned may have led to 3,400 (95%CrI: 1,300-4,400) peak daily hospital admissions under our central parameter scenario. Delaying until 19 July reduced peak hospitalisations by three-fold to 1,400 (95%CrI: 700-1,500) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to estimates of vaccine effectiveness and the intrinsic transmissibility of Delta. InterpretationOur findings show that the risk of a large wave of COVID hospitalisations resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with Delta, it may not be possible to fully lift NPIs without a third wave of hospitalisations and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FundingNational Institute for Health Research, UK Medical Research Council, Wellcome Trust, UK Foreign, Commonwealth & Development Office. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed up to 23 July 2021 with no language restrictions using the search terms: (COVID-19 or SARS-CoV-2 or 2019-nCoV or "novel coronavirus") AND (vaccine or vaccination) AND ("non pharmaceutical interventions" OR "non-pharmaceutical interventions) AND (model*). We found nine studies that analysed the relaxation of controls with vaccination roll-out. However, none explicitly analysed real-world evidence balancing lifting of interventions, vaccination, and emergence of the Delta variant. Added value of this studyOur data synthesis approach combines real-world evidence from multiple data sources to retrospectively evaluate how relaxation of COVID-19 measures have been balanced with vaccination roll-out. We explicitly capture the emergence of the Delta variant, its transmissibility over Alpha, and quantify its impact on the roadmap. We show the benefits of maintaining NPIs whilst vaccine coverage continues to increase and capture key uncertainties in the epidemic trajectory after NPIs are lifted. Implications of all the available evidenceOur study shows that lifting interventions must be balanced carefully and cautiously with vaccine roll-out. In the presence of a new, highly transmissible variant, vaccination alone may not be enough to control COVID-19. Careful monitoring of vaccine uptake, effectiveness, variants, and changes in contact patterns as restrictions are lifted will be critical in any exit strategy.

Excess mortality during the first ten months of COVID-19 epidemic at Jakarta, Indonesia (preprint)

Excess mortality during the COVID-19 epidemic is an important measure of health impacts. We examined mortality records from January 2015 to October 2020 from government sources at Jakarta, Indonesia: 1) burials in public cemeteries; 2) civil death registration; and 3) health authority death registration. During 2015-2019, an average of 26,342 burials occurred each year from January to October. During the same period of 2020, there were 42,460 burials, an excess of 61%. Burial activities began surging in early January 2020, two months before the first official laboratory confirmation of SARS-CoV-2 infection in Indonesia in March 2020. Analysis of civil death registrations or health authority death registration showed insensitive trends during 2020. Burial records indicated substantially increased mortality associated with the onset of and ongoing COVID-19 epidemic in Jakarta and suggest that SARS-CoV-2 transmission may have been initiated and progressing at least two months prior to official detection. Article summary lineAnalysis of civil records of burials in Jakarta, Indonesia showed a 61% increase during 2020 compared to the previous five years, a trend that began two months prior to first official confirmation of SARS-CoV-2 transmission in the city.

Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: a hospital-based retrospective cohort study (preprint)

BackgroundData on COVID-19-related mortality and associated factors from low-resource settings are scarce. This study examined clinical characteristics and factors associated with in-hospital mortality of COVID-19 patients in Jakarta, Indonesia, from March 2 to July 31, 2020. MethodsThis retrospective cohort included all hospitalised patients with PCR-confirmed COVID-19 in 55 hospitals. We extracted demographic and clinical data, including hospital outcomes (discharge or death). We used Cox regression to examine factors associated with mortality. FindingsOf 4265 patients with a definitive outcome by July 31, 3768 (88%) were discharged and 497 (12%) died. The median age was 46 years (IQR 32-57), 5% were children, and 31% had at least one comorbidity. Age-specific mortalities were 11% (7/61) for <5 years; 4% (1/23) for 5-9; 2% (3/133) for 10-19; 2% (8/638) for 20-29; 3% (26/755) for 30-39; 7% (61/819) for 40-49; 17% (155/941) for 50-59; 22% (132/611) for 60-69; and 34% (96/284) for [≥]70. Risk of death was associated with higher age; pre-existing hypertension, cardiac disease, chronic kidney disease or liver disease; clinical diagnosis of pneumonia; multiple (>3) symptoms; and shorter time from symptom onset to admission. Patients <50 years with >1 comorbidity had a nearly six-fold higher risk of death than those without (adjusted hazard ratio 5{middle dot}50, 95% CI 2{middle dot}72-11{middle dot}13; 27% vs 3% mortality). InterpretationOverall mortality was lower than reported in high-income countries, probably due to younger age distribution and fewer comorbidities. However, deaths occurred across all ages, with >10% mortality among children <5 years and adults >50 years.

Quantifying the dynamics of COVID-19 burden and impact of interventions in Java, Indonesia (preprint)

Measuring COVID-19 spread remains challenging in many countries due to testing limitations. In Java, reported cases and deaths increased throughout 2020 despite intensive control measures, particularly within Jakarta and during Ramadan. However, underlying trends are likely obscured by variations in case ascertainment. COVID-19 protocol funerals in Jakarta provide alternative data indicating a substantially higher burden than observed within confirmed deaths. Transmission estimates using this metric follow mobility trends, suggesting earlier and more sustained intervention impact than observed in routine data. Modelling suggests interventions have lessened spread to rural, older communities with weaker healthcare systems, though predict healthcare capacity will soon be exceeded in much of Java without further control. Our results highlight the important role syndrome-based measures of mortality can play in understanding COVID-19 transmission and burden.