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Coconut SurveillanceReal-time Surveillance and Response for Malaria Elimination1Part I: ContextPart II: The Case of ZanzibarPart III: Scaling-Up Coconut Surveillance

www.rti.org

RTI International is a registered trademark and a trade name of Research Triangle Institute.

Presenter: Richard Reithinger

2Part I: Context

Malaria Is a Global KillerSource: World Health Organization, Global Health Observatory Data Repository3

But Malaria Is Preventable and CurableMalaria-Free, Eliminating, and Controlling Countries, 201211. Source: UCSF Global Health Group, Malaria Elimination Group4

Key Element for Elimination: Top-notch SurveillanceMain challenges of malaria surveillance

Knowing where cases areDetermining distribution and clustering of cases in space and timeAbility to respond following case detectionTargeting limited resources for maximum impactPreventing reintroduction

Detection at this level requires enhanced resolution below the district level

Elimination and eventually certification can only be met with high resolution information systems and robust case detection and management processes

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6Part II: Zanzibar A PMI-supported Case Study for Successful High Resolution Surveillance

Presenter: Jeremiah Ngondi6

The Case of Zanzibar7East Africa2 large islands (Unguja, Pemba)A semi-autonomous part of the United Republic of Tanzania

Malaria Control Phases in ZanzibarHealth facility trends: Malaria confirmed cases and test positivity rate (19992014)

Gain after ACT introduction and before scale-up of mosquito control

Gain before ACT introductionNearing Malaria Elimination: for the third time1. Source: Zanzibar Malaria Elimination Program8

This graph shows the dramatic decrease of malaria in Zanzibar.The blue bars show the number of confirmed cases.The brown line shows the positivity rate. This is a commonly used indicator of the incidence of malaria.As we can see, this was has been reduced from more than 40% in 1999 to less than 1% in 2014.The red line at 5% is the threshold used by the World Health Organization to classify a country as being in the pre-elimination phase.The shaded rectangle shows the gain or reduction before the introduction of Artemisinin Combination Therapy (ACT), the recommended combination for malaria in Africa.The green shaded rectangle shows the gain after the introduction of this treatment, and before the scale-up of mosquito control programs.Mosquito control programs include spraying the inside of buildings with long-lasting insecticide, distributing bed nets treated with long-lasting insecticide, treating standing water to kill mosquito larva, and, where possible, eliminating standing water where mosquitos breed.The shaded rectangle in the lower right corner shows that malaria has nearly been eliminated; then we begin to see repeated seasonal spikes during the rainy season. This is the third time that Zanzibar has nearly eliminated malaria.They are very close to achieving their goal.8

But there are challenges9Decreasing effectiveness of vector controlPopulations decreasing perception of malaria riskCase importation from mainland TanzaniaAn effective surveillance and rapid response system is essential to addressing these challengesUsing dwindling resources more effectively

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Malaria Early Epidemic Detection System (MEEDS)In 2008 MEEDS broke ground in mHealth systems.

Health facility officers in clinics used simple cell phone handsets to submit weekly aggregated case data.

This enabled Zanzibar to detect new epidemic outbreaks within two weeks of onset.

This was a breakthrough for the Zanzibar Malaria Control Program.

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Malaria Early Epidemic Detection System (MEEDS)1110 sites in 2008

52 sites in 2009

90 sites in 2010

Now used by all public healthcare facilities in Zanzibar (157)

Now deployed to 77 (100%) of all private healthcare facilities

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But as we move from control to elimination12As malaria burden continues to decrease in countries and these countries move toward pre-elimination, there will be an increasing need to track and follow up individual malaria cases to limit onward transmission that could lead to outbreaks or broader resurgence.1Aggregate data are not sufficient1Presidents Malaria Initiative Strategy, 2015-2020We must be able to respond quickly and contain outbreaks effectivelyWe must be able to target limited resources for maximum impact

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What does it take to track and follow-up individual cases13

Better informed and more effective case management

Timely individual case notification

Risk-based active case detection

Identifying unreported cases in and around index case households

Geo-located case data

Real-time data collection, visualization, and analysis

Timely information for precisely targeting interventions

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Imagine a system that14Requires minimum local infrastructure

Works offline or online

Synchronizes case records across mobile devices, even when they are only occasionally connected

Interoperates with other leading systems used world wide

Can be deployed rapidly

Can be sustained locally

Is open

Presenter: Gordon Cressman

We imagined a surveillance system that requires minimal local infrastructure;Worked ofline or online;Synchronized case records across mobile deviceds, even when they only occasionally had connectivity;Interoperated with other leading tools and systems used world wide;Could be rapidly deployed, and locally sustained.RTI had aready invested in building a mobile platformthat met many of these these basic requirements.14

From MEEDS to15

Like the systems used in most PMI countries, MEEDS was a simple weekly reporting system for aggregated malaria data.It used simple, common, feature phone handsets to report these data from public health facilities.It also provided summary feedback to district medical officers and central program managers.As Zanzibar moved from control to surveillance, we built on this system to produce15

Coconut Surveillance16

Coconut Surveillance, a mobile system for tracking and following individual malaria cases.We added individual case notification to MEEDS.We worked closely with what was now the Zanzibar Malaria Elimination Program to develop a mobile application that could guide surveillance officers as the responded to each case, to provide ZAMEP with real-time data needed for high-resolution targeting of interventions.Notice how Detect is now a much small

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Where does Coconut fit into the health information system?17

Aggregated dataSimple case dataDisaggregated data

This diagram represents the architecture of something called the Open Health Information Exchange (OpenHIE).OpenHIE is not a piece of software, but is a set of standards for moving data from one component or system to another.The horizontal pipe that you see in the middle of this diagram represents that set of standards.The OpenHIE concept grew out of work in Rwanda and is being supported by a group of participating organizations that includes RTI.Above the pipe we see some core registries and services, a shared health record, and in the upper right, DHIS2.DHIS2 is now used in 47 countries.DHIS2 is designed for collecting, managing, analyzing, visualizing, and reporting aggregate health indicator data.DHIS2 is used to manage the national health data warehouse.RTI has supported development and implementation of national health information system strategy in Tanzania and Zimbabwe now for more than five years.This has included supporting the national roll-out of DHIS2 in both countries.DHIS2 also has and event module called Tracker designed to track and manage simple case data.However, DHIS2 tracker is not designed to replace electronic medical record systems and is not designed for disease surveillance and response.Below the pipe we see several examples of tools and systems designed to collect and manage disaggregated data.These include medical record systems, disease surveillance and response systems, and simple patient tracking systems, such as DHIS2 Tracker.We also see DHIS2 Mobile, which is represents two different DHIS2 mobile applications designed for collecting and reporting aggregate health indicator data to DHIS2.With the exception of DHIS2 Mobile, these systems collect and manage disaggregated data and then transmit aggregate indicator data to DHIS2.Coconut Surveillance is the only one of these systems designed specifically for tracking and responding to individual malaria cases and proven at scale in a malaria elimination context.We can return to this diagram later. For now, lets see how Coconut Surveillance is used to respond to a case.17

Detecting18

RTI has worked closely with the Zanzibar Malaria Elimination Programme (ZAMEP) to create a unique malaria case notification and mobile rapid response system. It has been used for more than two years. Lets see how it works.

Its Wednesday, and feeling awful, Siti and her mom decide to head to the doctor. Its at Charawe Heath Facility that Siti first will learn that she has malaria.From the health facility, Siti receives ACT, the recommended treatment for P. falciparum malaria. She is instructed to take the medicine for three days.A clinician at the health facility enters basic information about this new case by responding to an interactive SMS text messaging system. This enters the case alert into the system.18

Responding19

Shabani Khamis is one of 20 District Malaria Surveillance Officers serving Zanzibars 10 health districts.Instantly, Shabani receives an SMS notification on his phone that a new malaria case has been identified in Central District, where he serves. He opens the Coconut Surveillance application on his Android tablet to retrieve and view the new case record.Shabani will be the first to respond to Sitis malaria case.On his motorbike, Shabani rides off with a backpack containing medical supplies, including RDTs, and bed net vouchers. He also has the Coconut Surveillance mobile application on his tablet. He will use this to collect data as he follows up on this new case.

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At the facility

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First, Shabani visits the Charawe Health Facility, where he verifies the reported case and gathers additional information.A medical provider gives Shabani additional patient information for Siti, including a phone number and address where he can reach her.He enters the information collected into the Coconut Surveillance application on his tablet.

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At the household21

Shabani finds Siti and her mom at their home. First, he checks in with Siti to see how she is feeling and to make sure she is taking her prescribed medicine.Then he begins testing all members of the householdas long as they are homefor malaria infection using rapid diagnostic strip tests (RDT).Malaria is transmitted from one infected family member to another as mosquito vectors commonly feed on multiple people within a household. By detecting and treating cases early, Shabani ensures that the disease transmission stops with Siti.

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Testing and treating household members22

Pricking the finger of Sitis mother, Shabani draws a small drop of blood and places it on the rapid diagnostic strip test. He also takes her temperature.If any household members test positive for malaria, Shabani will give them medication (ACT) on the spot.Secondary malaria cases are being detected and treated in record time, often within 48 hours and before clinical symptoms are even presented.

Shabani then assesses the household and its surroundings for any environmental and household factors that may be conducive to malaria transmission. He drains any standing water and checks for the presence of window screens and for when the household was last sprayed with residual insecticide (IRS).Before he leaves, Shabani makes sure that Sitis family has enough long-lasting insecticide-treated bed nets (ITNs) to protect the entire family from mosquitoes and malaria.He pauses outside the house to record the geo-location and wirelessly sends the data collected during his household visit over the mobile network to a cloud database for further analysis and reporting.

Recording precise household location is valuable. These data are the difference between only knowing that malaria is in a health facility's catchment area (could be 10 square kilometers) and the location of the household (within 10 square meters). Being able to pinpoint response saves a lot of money. Data collected on the tablet are synchronized over the mobile phone network with a shared cloud database.

Synchronizing the data23

Data synchronization can be done manually or automatically, in the background.In Zanzibar, each user normally synchronizes data more than once a day over the mobile network.In other countries, where we have similar applications and mobile phone coverage is less extensive, users may synchronize data whenever they have mobile network coverage or they return to a location with a Wi-Fi access point23

Synchronizing the data

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Synchronizing the data25Many mobile data collection tools permit data to flow in one direction onlyBi-directional synchronization provides data to the mobile user, and enables a data-driven response

Data-driven response?26Guiding the mobile user based on real-time information and current response protocol.

Synchronizing the data27

All users in the same area or group (e.g. district) have mobile access to the same pool of case data. Two or more users can collaborate on the same case.

A user can transfer a case to another person.

Synchronization keeps track of all versions and can manage conflicts if they occur.

Monitoring the Process and Analyzing the DataDashboard to monitor response to each case

Maps of case households

13 built-in reports, most with drill down to case detail

Alerts generated automatically in real- time, at defined intervals, when thresholds are crossed, and errors are detected

Routine reports and alerts sent to users automatically via email and SMS

Data export to Excel28

Presenter: Jeremiah Ngondi

Back at the office, ZAMEP staff are able to access data for Siti and her household as well as any new malaria case data in all of Zanzibar along with the GPS locations for each.Supervisors uses a web dashboard to track the progress of the response to each new case nearly in real-time.Managers and supervisors use maps that enable drill-down to individual case data.The maps help managers to identify hot spots and transmission patterns.There is also an extensive set of dynamic reports developed in close collaboration with ZAMEP.The data can be exported easily for analysis using other tools.28

Pemba Island Trends of Timeliness of Weekly Reporting 2008 - 201529Unguja Island

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Trends of Weekly Malaria Cases 2008 -- 201530Pemba IslandUnguja Island

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Timeliness of Case Follow-up after Facility NotificationNumber of casesProportion of cases (%)31

Geographic Distribution of Malaria in 2015 (Jan--Aug)

Incidence of malaria per 1,000 populationGeo-location of malaria cases History of travel outside Zanzibar

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Visualizing Cases in Space and Time33Hi resolution heat map showing cumulative malaria cases in the Stone Town area of Zanzibar from June 2014 through February 2015. Intense foci appear as red areas.

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Data Analysis, Capacity Building and ResponseWorking with Zanzibar Malaria Elimination Program:

Defining epidemiological and operational triggers for action

Targeting of interventions for malaria elimination

Epidemic preparedness and response

Internal and external programmatic monitoring

Preventing re-introduction of cases

Secondary analysis of evidence base for wider malaria elimination agenda

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Presenter: Jeremiah Ngondi34

Coconut Surveillance at Scale

351,948 new cases,including asymptomatic cases, detected and treated (for every 4 cases at facility level, 1 case at household level)RDTs administered and data collected from 34,500+ household membersUsed to respond to 8,000+ malaria case reportsAll 20 district malaria surveillance officers use Coconut SurveillanceAll 157 government primary care units use Coconut SurveillanceDeployed to 77 (100%) of private clinics

Coconut Surveillance has been in use for more than two years.

In Summary36UniqueDesigned and developed in Africa by malaria experts

for reactive and active case detection, and

high-resolution targeting of interventions.ProvenUsed by Zanzibar for more than three years at scaleAdaptableRequires minimal technology

Can be adapted easily to local requirements

Surveillance officers learn to use it quickly++

Presenter: Richard Riethinger36

37Part III: Scaling up Coconut Surveillance

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Meeting Critical Surveillance System NeedsPMI Portfolio$4.5B+ invested in malaria programming since 200650+ implementing partners, many of which are involved in service delivery or surveillance activities

ImagineEach would develop their own electronic reporting and surveillance systems, fully staffed and supported Inconsistent quality of systems, data and serviceLack of interoperability between systems

Ideal SituationPMI supported programs all can have access to a platform that allows tracking and follow-up of individual malaria cases PMI has visibility through a standardized platform into its supported enhanced malaria surveillance efforts across all implementing partners in all focus countries

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Core Competency and Ease of Scale-UpCore Competency

Malaria implementing partners and stakeholders are primarily public health experts, not software developers

They want outputs

Coconut Surveillance has been developed with PMI funds harnessing ICT and malaria experts knowledge and experiencePlatform has been operational for 3+ years

Ease of Scale-upMinimal requirements are needed (e.g. phones or tablets), differences mainly dependent on in-country telecommunications providersInteroperates with other leading systems used world wideCan be deployed rapidly and sustained locally39

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Technology alone is not the solutionTechnical assistance service package is needed to ensure:

Consistency and quality of dataRight feedback loops are in place (e.g. triggers, events) that allow people to act on data and capacitate them to distinguish noise from triggers / eventsTechnical expertise to analyze and act upon the dataTechnical expertise to adapt, operationalize and improve platform to relevant country contexts

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What would be scale-up costs?41Zanzibar

ICT System (current per year) $50,000 for system implementation and support $45 per facility (234) $510 for each DMSO (20)

Other Costs (covered by ZAMEP & PMI) Motorbikes Training Staff salaries: DMSOs and District Response Teams Interventions Technical assistance for data analysis and action

This innovative disease surveillance and risk-based rapid response system will be unique in malaria elimination.It has several characteristics that make it easy to adopt and scale.

First, it is built entirely using free and open source software technology, and will remain free and open source. There are no licensing fees.

Second, it is inexpensive to operate and scale.It costs less than $350 each year for cloud hosting for Zanzibar.It costs less than $510 each year per mobile user, and less than $10,200 each year in Zanzibar for 20 users.

It is quick and easy to adopt, Adaptable to different case alert systems and to other diseases.And the technology scales easily.

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Questions and Discussion42While the progress to date is historic, the continued control and ultimate elimination of malaria remains fraught with serious challenges, including resistance to the artemisinin family of drugs, wide availability of substandard and counterfeit malaria treatments, resistance to key insecticides, inadequate disease surveillance systems, and waning country and donor attention as malaria burden drops.1 1Presidents Malaria Initiative Strategy, 2015-2020

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