Association between SKDR dashboard utilization and officers’ perceived early detection of increased dengue cases in gunungsitoli city: Cross-sectional study
DOI:
https://doi.org/10.35335/midwifery.v14i4.2488Keywords:
DBD, Epidemiology, Health Information, System SurveillanceAbstract
Background: Dengue Hemorrhagic Fever (DHF) surveillance requires timely trend monitoring, alert identification, information verification, and public health response. The Early Warning and Response System (SKDR) dashboard provides data to support these steps. Objective: To analyze the association between SKDR dashboard utilization and officers’ perceived early detection of increased dengue cases in Gunungsitoli City in 2026. Methods: This analytical quantitative cross-sectional study was conducted at the Gunungsitoli City Health Office and eight UPTD Puskesmas, involving 95 surveillance officers engaged in dengue surveillance. Structured questionnaires measured dashboard utilization (four dimensions) and perceived early detection (four indicators), each scored 0–100 and grouped into categories, including adequate. Validity was tested using corrected item-total correlation and reliability using Cronbach’s alpha. Data were analyzed univariately, bivariately using Pearson correlation, and multivariately using multiple linear regression. Results: Mean utilization was 73.47 (adequate 60.0%), and mean perceived early detection was 74.52 (adequate 57.9%). Most officers (87.4%) had never attended SKDR training. Utilization correlated very strongly with perceived early detection (r=0.873; p<0.001). After adjusting for SKDR training, working period, internet access, SOP/supervision, and number of officers, utilization remained associated (B=0.927; β=0.874; p<0.001; adjusted R²=0.875). Conclusion: Higher dashboard utilization was associated with higher perceived early detection of increased dengue cases. Because both variables were self-reported from the same respondents, the association may be inflated, and the cross-sectional, single-city design prevents causal or generalizable conclusions. Strengthening SKDR training, supervision of alert verification, and data-based follow-up is recommended; future studies should use recorded alert-verification times.
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