Regression-based Model Deciphers Progression on Health Management for Two Long-standing and Unresolved Infectious Diseases in Indonesia: Integration of Outpatient Data by the National Universal Health Care (BPJS) and Fluctuation of Registered HIV and Malaria Cases

¹ Mathematics Departement, School of Computer Science, Bina Nusantara University, Jakarta Barat - Indonesia
² Information System Department, BINUS Online Learning (BOL), Bina Nusantara University, Jakarta Barat - Indonesia
³ National Research and Innovation Agency (Badan Riset dan Inovasi Nasional, BRIN), Tangerang Selatan - Indonesia

^* Corresponding author: ika.nurlaila@brin.go.id

Abstract

Although the COVID-19 outbreak was recently declared overcome COVID-19 is not the sole life-threatening infectious disease for which we direct our all resources. HIV and malaria are, on the other hand, two long-standing national health issues that are yet to find a proper solution. We query how these two infectious diseases load volume on National Burden as represented by the claims National Health Resilience and how far our efforts paid thus far affect the progression on optimally putting the cases in a break. We approach these mathematically as we hardly found integrated reports on this matter. Hence, we employed regression linear to model the Health Resilience of Indonesia based on the dynamics of outpatients and inpatients across facility categories (class) provided by National Universal Health Care (BPJS) in the context of HIV and malaria infection cases respectively. The estimation of the two regression parameters was done via the ordinary least square (OLS) method. We used pandas 1.3.5 for performing the data analysis, seaborn 0.11.2 and matplotlib 3.5.1 for the data visualization, and scipy 1.7.3 and statmats 0.31.2 for the statistical analysis. Our results show that the number of outpatients declines as the number of HIV and malaria cases increase. Furthermore, we obtained significant associations between the increased HIV rate and decreased number of outpatients in class 2 (P=0.030), class 3 (P=0.002), and the total outpatients (P=0.0019). These patterns are not observed for malaria cases. Meanwhile, the increase in HIV cases was found to be associated with the decreased number of registered BPJS in class 1 (P=4e-4), class 3 (P=1.5e-6), and total participants in all classes (P=3.6e-6). Less strong associations were found between the malaria cases with decreased number of participants in BPJS class 1 (P=0.010), class 3 (P=0.042), and the total registered to BPJS (P=0.045). Our data suggest that the higher the HIV incidence rate the lesser likelihood of the affected patients being treated as outpatients using facility classes 2 and 3 since this may lose the transmission control intervention. Intriguingly, in the sense of the BPJS facility category where an increased HIV rate is seen to be strongly associated with a decreased registration number for class 1 and class 3, the monthly dues and the adequateness of expected facility items may be the most abductive reasoning. Despite our understanding that these require validation cohort, taken altogether our data hint the threat of HIV is steady and demands a new approach to strategizing for the sake of limiting the transmission as well as maintaining the quality of life of the affected patients.