Teledermatology to Improve Access to and Quality of Skin Care in Eastern Indonesia.

Skin diseases are a major public health concern in Indonesia, although access to specialized care in remote areas is limited. We initiated a low-cost teledermatology service in Sumba, a remote island in eastern Indonesia. Eighteen healthcare workers (HCWs) at five primary healthcare centers received training to manage common skin diseases and submit clinical cases beyond their expertise to an online platform. Submitted cases were reviewed by at least one dermatologist. Diagnostic agreement between HCWs and dermatologists was calculated. The HCWs participated in a satisfaction survey 2 years after project initiation. Since October 2020, of 10,384 patients presenting with skin complaints in a 24-month period, 307 (3%) were submitted for a teledermatology consultation. The most frequent skin diseases were infections and infestations (n = 162, 52.8%) and eczematous (85, 27.7%) and inflammatory (17, 5.5%) conditions. Fifty-three patients (17.3%) were diagnosed with a neglected tropical skin disease, including leprosy and scabies. Dermatologist advice was provided within a median of 50 minutes (interquartile range, 18-255 minutes), with 91.9% of consultations occurring within 24 hours. The diagnostic agreement level between HCWs and dermatologists significantly improved over time, from 46.9% in the first 6-month period (κ = 0.45; 95% CI, 0.37-0.54) to 77.2% in the last 6-month period (κ = 0.76; 95% CI, 0.67-0.86; global P < 0.001). The HCWs reported that the teledermatology service was extremely/very useful in supporting daily practice (100%) and improved their knowledge of skin diseases tremendously/a lot (92%). Teledermatology can improve accessibility and quality of skin services in medically underserved areas, providing opportunities for scalability and knowledge transfer to frontline HCWs.

Quantifying spatial heterogeneity of malaria in the endemic Papua region of Indonesia: Analysis of epidemiological surveillance data.

Background: As control efforts progress towards elimination, malaria is likely to become more spatially concentrated in few local areas. The purpose of this study was to quantify and characterise spatial heterogeneity in malaria transmission-intensity across highly endemic Indonesian Papua. Methods: We analysed individual-level malaria surveillance data for nearly half a million cases (2019-2020) reported in the Papua and West Papua provinces and adapted the Gini index approach to quantify spatial heterogeneity at the district and health-unit levels. In this context, high Gini index implies disproportionately distributed malaria cases across the region. We showed malaria incidence trends and the spatial and temporal distribution of sociodemographic characteristics and aetiological parasites among cases. Findings: While Papua province accounted for the majority of malaria cases reported in the region and had seen a rise in transmission since 2015, West Papua province had maintained a comparatively low incidence. We observed that Gini index estimates were high, particularly when the lower spatial scale of health units was evaluated. The Gini index appears to be inversely associated to annual parasite-incidence, as well as the proportions of vivax malaria, male sex, and adults. Interpretation: This study suggests that areas with varying levels of transmission-intensities exhibited distinct characteristics. Malaria was distributed in a markedly disproportionate manner throughout the region, emphasising the need for spatially targeted interventions. Periodic quantification and characterisation of risk heterogeneity at various spatial levels using routine malaria surveillance data may aid in tracking progress towards elimination and guiding evidence-informed prioritisation of resource allocation. Funding: The study was funded by the Australian Government Department of Foreign Affairs and Trade Indo-Pacific Centre for Health Security through the Strengthening Preparedness in the Asia-Pacific Region through Knowledge (SPARK) project.

Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia.

INTRODUCTION: Worldwide, the 33 recognised 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 healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021. METHODS: This retrospective cohort included 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 subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality. RESULTS: Of 705 503 cases with a definitive outcome by 31 August 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 subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 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 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest). CONCLUSION: In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.