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

Dr Anette Hulth, Karolinska Institutet, SwedenDr Vanessa Quan, National Institute for Communicable Diseases, South AfricaDr Vishal Diwan, R.D. Gardi Medical College, Madhya Pradesh, India

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)

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

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

The South African branch of ISIS – ISIS Bush

Study site3 clinics in Bushbuckridge, Mpumalanga

• irregular access to telephone and fax lines • minimal access to computers and internet• good cell phone coverage

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

ISIS-Bush – in more detail

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

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

Evaluation

• technical evaluation (simplicity, flexibility and usability)

• timeliness of reporting• acceptability of the surveillance

system

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)

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.

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.

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.

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”

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

The Indian branch of ISIS – ISSI

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

Target diseases 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

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

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

Study objectives

To test a mobile-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, usability and acceptability

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)

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

Reports on: Respiratory infectious diseases Gastrointestinal infectious diseases

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

Smart phones

The data entry was like filling out the paper form

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 private health 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

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

• Huge underreporting in IDSP• Data from 8 providers • >4,500 informal providers only in this district

Results: IDSP vs present study

Evaluation of system performance Qualitative evaluation of system

• usability • stability • acceptability

Focus group discussion with data collectors Questions on battery and connectivity

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.”

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

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.”

Evaluation: acceptability

GIS map showing location of provider and location of patients

Patients from >400 villages

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.

Two branches – one project

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!