Development of GIS-based software
Malaria Control System is a state of the art suite of software product to transform existing programme in the Mangaluru city into a technology driven intelligence-assisted programme. Between August 2014 and September 2015, a software programme was designed for effective micro-implementation of all anti-malarial activities (Fig. 1). At the core, this system is a GIS-tagged mobile app for civic body field force for reporting and monitoring of incident cases as per the NVBDCP guidelines, mosquito breeding site reporting and intervention monitoring [13]. Civic body, geographical and administrative structures are mapped into the software for efficient monitoring, workload allocation and reviews. It has an online (web) app for healthcare providers (hospitals, diagnostic clinics etc.) to report malaria cases, and submit statutory reports. Back end data is automatically generated to excel sheet and analyses were carried out to identify the hot spots, high risk wards, and also fortnightly/monthly trends. Another online (web) app is also linked to analyse effectiveness, identify issues and defaulters, and take timely administrative actions.
Figure 2 describes various components of the software and its functionalities. Important salient features of software are: (a) all stakeholders instantaneously connected soon after case details are entered on the website, thereby translate reporting into field action; (b) facilitates geospatial mapping; (c) mandatory closure of cases, and also interventions of mosquito breeding habitats after effective completion of action; (d) document evidences of field activities and parasite clearance time. Briefly, programme incorporates most strategies for malaria from surveillance to complete treatment along with vector control activities—a distinct viable solution.
Introduction of digital TABs in malaria surveillance
In the digital India era, most of the health staffs have experience in using Android-based smart phones. This helped in better understanding of the operational procedures of the working systems. Initially, field trials were carried out to study the operational feasibility and troubleshooting along with enhancement of systems. Eight MPWs were given hands-on training in the field during field trials, and these trained MPWs in turn trained other 54 MPWs in the field. In October 2015, the programme was scaled up to cover the entire city of Mangaluru spread over in 60 wards (Fig. 2). Additional training was carried out in the field for the needy ones. Separate workshops and training programmes were conducted for laboratory technologists, MPWs and hospital authorities both in private as well as public health systems for reporting of cases before scaling up of the programme to the entire city. At present the programme is governed and maintained by the local civic authorities.
Malaria control programme after digitization
Malaria control operations in Mangaluru city were fully digitized in October 2015, and a network between diagnostic centres, field workers (MPWs) and administrators was established. As soon as a case of malaria was diagnosed in the field or any laboratories, hospitals and malaria clinics, assigned personnel were statutorily required to login and enter case information through online web portal into the software. Hospitals and clinics both in public and private health systems began to report malaria cases online. Information on newly reported cases was made available from the TAB devices provided to each MPW. Online entry of new case triggered an alert to these workers on their TABs who in turn mandatorily visited the households, meet patients and their families, ensure complete treatment and survey the neighbourhoods. These TABs are loaded with software/app which provided them information regarding anti-malarial activities to be carried out as per the NVBDCP guidelines. Activities included search for source of mosquito breeding sources, collection of blood smears from any fever case in and around malaria-positive households. MPWs were instructed to record all their visits and activities on their devices. It was mandatory for them to close each malaria positive case and mosquito breeding sources after complete action in the field. GIS-tagged patient information helped the MPWs to visit these houses and record pre-determined information about cases and field activities. The activities and movements of the MPWs were monitored through GIS.
City corporation executives were motivated to use only data from the online system for their reviews and presentations instead of the data from manual records and registers. Currently, 70 field workers (MPWs, Health Supervisors) and 85 health care providers (hospitals, clinics, and diagnostic centres) are using these apps/solutions.
Secondary data (pre- and post-digitization) analysis
Study design
Process of digitization
This is an uncontrolled field trial to know the impact of application of digitization software on operational parameters of malaria control as compared with situation before interventions. All cases of malaria reported in the geographical area of Mangaluru Municipal Corporation were included in the study. Cases diagnosed by the local diagnostic labs, hospitals, malaria clinics, and also surveillance teams, by microscopic examination of blood smears, rapid diagnostic test (RDT) kits and quantitative buffy coat (QBC) fluorescent technique were also included.
Between October 2014 and September 2015 digitization year (DY) when software was conceived, codes were written, programme was developed, field trials were conducted and all the activities carried out were manually documented. First year post-digitization is considered as PDY1 (October 2015 to September 2016), and second year post-digitization is represented as PDY2 (October 2016 to September 2017). Post-digitization is the phase when the software was accepted and well utilized by all the stakeholders namely diagnostic laboratories, hospitals, field workers and administrators.
Data inputs
Both active and passive surveillance data, case management details, anti-larval activities undertaken, were considered as real-time digital data on the system from September 2015 onwards. Manually compiled data for 1-year period during digitization phase from October 2014 to September 2015, and a year prior was obtained from malaria control cell of city administration.
Data analysis
Collected data were analysed as follows:
- 1.
To assess improvement in surveillance reporting time, and field action.
- a.
Time taken to report a malaria positive case. This indicated reporting behaviour of health workers and facilities (laboratories, clinics and hospitals). This was carried out as back end analysis in the first 15 months after implementation.
- b.
Closure of cases after complete treatment. A case is closed after revisit to their residences, and documentation of evidences for post-treatment parasite clearance time. Number of cases closed indicated completion of treatment and negative blood smear post-treatment of active surveillance around reported case (ASARC). Routine and mandated house visits in the houses of the malaria cases; contact blood smears in surrounding households; identification of mosquito breeding sites and their elimination were conducted.
- c.
Number of contact blood smears collected in fever cases around the reported case.
- d.
Annual blood examination rate (ABER) as an indicator for effective surveillance.
- 2.
To assess the effectiveness of interventions.
- a.
Surveillance and malariometric indices: Annual Blood Examination Rate (ABER), Annual Parasite Incidence (API), Slide Positivity Rate (SPR), Slide Falciparum Rate (SFR), Percentage of P. falciparum cases (Pf%), and total number of cases reported.
- b.
All indices were compared with available manually collected data of 1 year prior to digitization (Pre-DY).
Statistical analysis
Data are represented as descriptive data, trends and Chi-square test was applied wherever appropriate using VassarStats (vassarstats.net) analysis tool. Significance values p < 0.05 was considered significant.