Mobile-based surveillance of infectious diseases in South Africa and India

1. Mobile-based surveillance of infectious diseases in South Africa and India Dr Anette Hulth, Karolinska Institutet, Sweden Dr Vanessa Quan, National Institute for CommunicableDiseases, South Africa Dr Vishal Diwan, R.D. Gardi Medical College, Madhya Pradesh, India

2. The ISIS project (i) • Focuses on early detection and monitoring of infectious disease epidemics in resource-limited areas • Coordinated by Karolinska Institutet • Collaborating partners: • National Institute for Communicable Diseases, South Africa • R.D. Gardi Medical College, Madhya Pradesh, India • Swedish Institute for Communicable Disease Control (now Public Health Agency of Sweden)

3. The ISIS project (ii) • Funded by the Swedish Civil Contingencies Agency (MSB) and the Swedish International Development Cooperation Agency (SIDA) • Three years + an extension of nine months • Formally started on January 1, 2011

4. ISIS – general set up • The focus is on the technology • The selected means of reporting is by smart phone • Reporting is implemented from the primary health care level

5. The South African branch of ISIS – ISIS Bush

6. 3 clinics in Bushbuckridge, Mpumalanga Study site • irregular access to telephone and fax lines • minimal access to computers and internet • good cell phone coverage

7. ISIS-Bush – in more detail • The reporting was done for selected data already collected in a paper-based manner at the clinics • The reports were submitted by mobile phone to those who currently obtain these data • As we were foremost evaluating the feasibility and the technical aspects, a designated person did the reporting • Reporting was done from October 2012 – May 2013

8. The malaria program (i) • The monitoring and evaluation target indicators in the malaria elimination strategy include: • notification of all malaria cases within 24 hours of diagnosis at all public and private health care facilities (to the district level) • investigation within a case’s household and neighbouring households within 48 hours of notification • reporting of each case to provincial and national level within 72 hours of notification

9. The malaria program (ii) • The district level is experiencing a problem with late reporting from the area, which is one of few malaria endemic areas in South Africa • We used a smart phone for the data submission • Patient-level data on each positive malaria case, as currently reported within the malaria program • Additionally, an sms alert was sent to the malaria team coordinator in the district

10. Evaluation • technical evaluation (simplicity, flexibility and usability) • timeliness of reporting • acceptability of the surveillance system

11. Timeliness • If the time from diagnosis to entering the case information into a central database was different with the mobile reporting in place • If the time it took from diagnosis to follow up was affected by the mobile reporting: • the time it took for all cases to be followed up after diagnosis • the proportion of cases that were followed up within the required time (48 hours)

12. Results: timeliness (i) 24 reported cases during the study period (8 months) For n=23 we obtained complete data -> With the sms: 18 (75%) cases were notified to relevant stakeholders within 24 hours; the other 5 were diagnosed on weekends or during public holidays when our nurse was off.

13. Results: timeliness (ii)Time between diagnosis and case information being entered into central information system -> The complete case information was entered two to three weeks earlier with the mobile reporting than from other clinics.

14. Results: timeliness (iii)Time between diagnosis and follow up -> In 2011/2012, one case out of 22 reported from the study clinics was followed up within two days. During the study period in 2012/2013, 15 cases out of 23 were followed up within two days. For the other clinics in the area, only a small improvement was seen between the two periods.

15. Results: acceptability • An sms alert reduces the transport costs for the case investigators • “With the sms alerts [the case investigator] came immediately for positive cases”, and “much quicker than normally”

16. Conclusions malaria surveillance • Surveillance by smart phones is acceptable and technically feasible in rural South Africa • The use of a notification sent via SMS from the mobile phone for each newly diagnosed malaria case improved the timeliness • Consideration should be given to large-scale use, possibly using a toll-free phone service, within the malaria control programmes • Would support the aim of malaria elimination by 2018

18. The Indian branch of ISIS – ISSI

19. Integrated Disease Surveillance Project (IDSP) in India • Objectives of IDSP: • Establish a decentralized system of disease surveillance for timely and effective public health action • Improve the efficiency of disease surveillance for use in health planning, management and evaluating control strategies • Implemented through the Central Surveillance Unit within the National Centre for Disease Control (NCDC) in New Delhi

20. Malaria ADD (cholera) Typhoid Tuberculosis Measles Polio Plague HIV, HBV, HCV Unusual syndromes Accidents Water quality Outdoor air quality NCD risk factors State specific diseases Target diseases

21. Gaps in the IDSP program in India • Not all health care providers report suspected or confirmed cases • Most health centres in the private sector do not provide data • 75% of all health care providers are found in the private sector • A high number of informal providers in the health sector

22. Informal health care providers • Represent a large portion of the health care system in India • Individuals living in rural parts are more likely to see an informal health care provider • Lacks state accredited medical qualification • Not legalized to practice allopathic medicine • Lack medical education but might have some medical training • Examine patients and prescribe medication

23. Study objectives • To test amobile-based syndromic surveillance system and its application in a resource-limited setting in rural India • To test the system on both formal and informal health care sectors • To evaluate mobile phone based syndromic surveillance platform in terms of its stability,usabilityand acceptability

24. Data collection (i) • 9 health centres – 6 of which were informal • By collecting data from informal providers, we got information that otherwise is unavailable • Study period: Jan–June, 2013 (6 months)

25. Data collection (ii) • A smart phone with 3G internet connection was provided to the data collectors (n=6) for data entry • An external server was hired for data storage • Entry could be done both in online and offline mode

26. Reports on: Respiratory infectious diseases Gastrointestinal infectious diseases

27. Collected data • health centre • visit date • age (years or month) • sex • city/village • symptoms • fever duration < 3 or > 3 days • body ache • pain in throat • runny nose • cough • headache • loose motion < 3 or > 3 days • pain in abdomen • nausea or vomiting • other

28. Smart phones • The data entry was like filling out the paper form

29. Results • Totally 21,326 patient encounters were recorded in the system • 20,424 were included in final analysis • 10% of the patients were up to five years of age • 83% of the patients visited the privatehealth care sector • 21% of the females visited the governmental health care provider compared to 14% of the males • 18% of the patients visiting the governmental health care provider were five years or younger, compared to 8% of the patients visiting any of the private providers

30. Total cases: 20,424 Fever: 9,770 Cough: 7,833 Diarrhoea: 1,942 Sore throat: 1,403

31. Results: IDSP vs present study • Huge underreporting in IDSP • Data from 8providers • >4,500 informal providers only • in this district

32. Evaluation of system performance • Qualitative evaluation of system • usability • stability • acceptability • Focus group discussion with data collectors • Questions on battery and connectivity

33. Evaluation: stability • Mostly good network connection • Even during days when they deemed the connection as good, the data collectors still experienced network problems “Once or twice in a day we used to have problem with the internet connection.” • Quality of mobile phones used for data collection “Initially it was good but slowly it started getting discharged very fast. We had to charge our battery morning two hours and evening two hours.”

34. Evaluation: usability • Five of the six data collectors used a smart phone for the first time • All data collectors felt comfortable with entering the data on the provided smart phone within a week • The offline mode that was added in the beginning of the study was appreciated by the data collectors “In offline we can do our work without internet and in online we have to again and again connect to a network. Time is saved in offline and more forms are filled in the given time.” • Issues with small screen of smartphones • Lack of feedback and usefulness of data at local level

35. Evaluation: acceptability • Health providers supported the data collectors, although some were reluctant in the beginning “They must have thought what we would do with this information. They must be scared that we would do some new project for their patients. Private doctors were scared but government doctors didn’t had this problem.” • Some data collectors wanted to collect more information than requested, and also saw the need for diagnoses-specific data collection “I had no problem in filling the forms but the only problem was that the questions were not adequate like there was no information on Malaria, TB or other big diseases. So, I used to write on my own in the bottom of the form.”

36. GIS map showing location of provider and location of patients Patients from >400 villages

37. Conclusions Indian branch • A mobile-based platform can be used for collecting syndromic surveillance data in resource limited settings • Network connection works sufficiently well, but offline entry option should be supported • Possible to collect syndromic surveillance data from the informal sector • Underreporting of cases with notifiable symptoms in IDSP data • Data can be used to better understand the health-seeking behaviour of those visiting informal providers.

38. Two branches – one project

39. Two continents – similar experiences • also people who haven’t used smart phones (or computers) before can in a short time be trained to fill out surveillance forms and submit those from the device • the technology works sufficiently well for these kinds of applications • it is what you do with the data that matters!