Objective: To analyse the effect of using digital health technology on leprosy control programmes.
Method: The systematic review comprised search on PubMed, Scopus, ScienceDirect, SAGE and ProQuest databases for interventional studies published in English language from 2013 to 2021 which used digital health technology for leprosy contact tracing, active leprosy detection, monitoring of multi-drug therapy and treatment management during the corona virus disease-2019 pandemic A standard risk of bias tool was used to evaluate bias in the studies, and the Joanna Briggs Institute protocol was used to assess the quality of the studies analysed.
Results: Of the 205 studies initially identified, 15(7.3%) were analysed in detail. Quasi-experimental studies had a low risk of bias compared to the rest. The e-leprosy framework was being used along with applications based on smartphones and artificial intelligence Digital health technology was found to be practical, accessible and effective in leprosy control programmes.
Conclusion: Studies reported favourable findings regarding the use of digital health technology in services related to leprosy patients.
Keywords: Prophylaxis, Leprosy, COVID-19, Nursing. (JPMA 73: S-170 [Suppl. 2]; 2023)
Leprosy, also known as Morbus Hansen (MH), is a contagious and chronic infectious disease caused by mycobacterium (M.) leprae. Early detection and treatment can cure leprosy and prevent disability. The World Health Organisation (WHO) noted that there were 12,558 new cases of leprosy detected globally in 2020, and there were 129,389 cases on treatment. The Indonesian Ministry of Health reported that there were 16,704 cases of leprosy and the proportion of new cases of leprosy in children in Indonesia had reached 9.14%.1,2
The impact of the coronovirus disease-2019 (COVID-19) pandemic in 2020-21 resulted in a decrease in the implementation of treatment programmes, and leprosy case discovery fell by 37% from the year before the pandemic.1 Leprosy patients who are supposed to make regular visits to public health centres had to go through complicated procedures due to the increasing number of COVID-19 cases. The symptoms of leprosy are white or red patches on the skin. The patches are not itchy or painful, but numb. Because they don’t feel pain or itching, the patients tend to be indifferent towards the treatment, which has the potential to transmit and cause disability.3
Short message reminders are proven to be effective in increasing the punctuality of taking medication (21%) and attendance at public health centres (14.6%) for leprosy patients. Mobile-phone-based health (M-Health) delivery has been proven to be effective in preventing stigma and exclusion from families and communities towards people with leprosy, and health technology is taken as a tool to make it easier for leprosy patients to undergo treatment protocols.4,9
The COVID-19 pandemic disrupted health services, thus opening up opportunities for the application of health digital technology in diagnosing, referring, monitoring and training health staff, providing treatment and managing disabilities.1
The current systematic review was planned to analyse the effect of using digital health on leprosy control programmes.
Materials and Methods
The systematic review comprised search on PubMed, Scopus, Science Direct, SAGE and ProQuest databases for interventional studies published in English language from 2013 to 2021 which used digital health technology for leprosy contact tracing, active leprosy detection, monitoring of multi-drug therapy (MDT) and treatment management during the COVID-19 pandemic.
The search protocol was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search strategy was in line with the Population-Intervention-Comparison-Outcomes-Time (PICOT) framework (Table 1), and key words used included pandemic, COVID-19, digital health, technology, and leprosy. Descriptive and quasi-experimental studies whose full texts were available were included.
A standard risk of bias tool was used to evaluate bias in the studies, and the Joanna Briggs Institute (JBI) protocol was used to assess the quality of the studies analysed.
Of the 205 studies initially identified, 15(7.3%) were analysed in detail (Figure 1).3-12,14,16-17,19-20
Overall, quasi-experimental studies had a low risk of bias (Figure 2).
The e-leprosy framework was being used to send messages repeatedly to patients, their relatives and the relavent leprosy surveillance officers (LSOs) every month regarding the due date for multi-drug therapy at the appropriate public health center.4 Every day across the duration of the treatment, the patient was being sent a reminder message to take medication.5 Also used for the purpose was the Mh-Mobile application.2 Health workers used artificial intelligence (AI) applications to screen leprosy.6 Use and development of RehApp, a digital tool for field force working with people with disabilities, and global positioning system (GPS) tracking devices to track mobility, to assess health-seeking behaviour and support contact tracing were also in use (Table 2).19
The WHO has developed an e-learning module aimed at improving the knowledge and skills of staff at all levels on topics ranging from referral and suspected diagnosis to leprosy treatment and disability management.1 People with leprosy may experience permanent disabilities related because of the involvement of skin, peripheral nerves, limbs and eyes, if they do not carry out the treatment programme.1
Studies3-5,7-8,16,19-20 found that digital health technology is very effective in helping early detection of leprosy contacts, finding active cases and disabilities, and even increasing adherence to medication among leprosy patients.
One study7 demonstrated the efficacy of a new computer design for lowering foot-load and improving compliance, while another9 reported that leprosy diagnostic tests through smartphone technology were faster than laboratory tests.
According to Cheng et al.10 the sensitivity of digital polymerase chain reaction (dPCR) test for detecting M. leprae deoxyribonucleic acid (DNA) was greater than quantitative PCR (qPCR), while Paul et al.11 reported that M-Health was effective in preventing stigma and exclusion of leprosy patients undergoing treatment, and Raza et al.14 found that the stochastic model was efficient, low-cost and feasible for leprosy management.
The current review was not registered with the international prospective register of systematic reviews (PROSPERO), which is a limitation.
Literature reported favourable findings regarding the use of digital health technology in services related to leprosy patients.
Acknowledgment: We are grateful to the Dean and Vice-Deans of the Faculty of Nursing, Universitas Airlangga, Coordinator of the Masters of Nursing Study Programme, Universitas Airlangga, and all those who helped during the process.
Conflict of Interest: None.
Source of Funding: None.
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