Transcript Improving malaria surveillance: Zambia’s experience with

Training Workshop: 2012
Web: www.nmcc.org.zm
Email: [email protected]
Overview
 Training Objectives
 National Malaria Strategic Planning Goals 2011-2015
 Improving the surveillance environment
 Background
 Solutions
 Progress to date and plans
 Opportunities
Training Objectives
Training Objectives contd …
 To orient district and health facility staff in Malaria
Rapid Reporting System
 To update participants in the mobile reporting
technology
Strategic Planning Goals
2010
 Reduction of malaria
incidence by 75 percent and
deaths significantly
reduced
 Through above, there will
also be a reduction in allcause mortality by 20
percent in children under 5
 Malaria control will also
provide economic payoffs at
the household and national
levels
2015
• Reduce malaria
incidence by 75
percent of the 2010
baseline
• Reduce malaria deaths
near zero and reduce
all-cause child
mortality by 20
percent
• Establish and maintain
five (5) “malaria free
zones”
Establishment of malaria free
zones
By 2015 have supported and documented
five (5) Zambia malaria free zones/districts
milestone:
- By 2013, malaria has been eliminated in
two (2) districts in Zambia
Measuring malaria progress
 Lots of information on malaria interventions and burden
(prevalence) in Zambia
 MISs, DHSs, other surveys
 Mainly national, not especially helpful for local decision
making
 Programmatic information
 ITN distributions to districts
 IRS structures targeted/sprayed
 Medical supplies (ACTs/drugs/RDTs) going out to facilities
through Medical Stores
 National routine reporting system
 HMIS recently revised to include additional indicators

Confirmed cases, patients tested, IPT
Stratification of malaria burden
 Based on national survey
data (3 MISs)
 Household level
microscopy prevalence
 Suggests consistently
much lower burden in
Lusaka, Southern and
Western provinces
 New Strategic Plan creates
3 tier stratification to
acknowledge this
Chienge
Kaputa
Mpulungu
Mbala
Nchelenge
Nakonde
Mporokoso
Kawambwa
Mungwi
Isoka
Mwense
Kasama
Luwingu
Chinsali
Chilubi
Chama
Mansa
Samfya
Mwinilunga
Milenge
Chililabombwe
Chingola
Mufulira
KalulushiKitwe
Ndola
Lufwanyama
Luanshya
Masaiti
Solwezi
Chavuma
Kabompo
Zambezi
Mufumbwe
Lundazi
Serenje
Mambwe
Mpongwe
Kasempa
Petauke
Chadiza
Nyimba
Kabwe
Lukulu
Chipata
Katete
Mkushi
Kapiri Mposhi
Kalabo
Mpika
Chibombo
Kaoma
Mumbwa
Mongu
Lusaka
Itezhi-Tezhi
Kafue
Namwala
Senanga
Shang'mbo
Siavonga
Choma Gwembe
Sesheke
Luangwa
Rate of malaria total cases
per 1000, by district, 2010
Mazabuka
Monze
Kazungula
Chongwe
0 - 4.9
5.0 - 9.9
10.0 - 19.9
Kalomo
Sinazongwe
20.0 - 99.9
Livingstone
>=100.0
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Driving transmission to near zero level
Universal LLIN coverage
STEP 1
Zambia Rapid Reporting system
Baseline transmission
STEP 2
Clear parasites from people
Mass Screen and Treat
STEP 3
Surveillance as an intervention
Reduced transmission
STEP 4
All cases identified, investigated and cleared.
Document elimination
Community case
management with
household rescreen and treat
Near-zero transmission
Adapted from WHO Global Malaria Programme: Community-based transmission reduction of malaria
May 2011 - DRAFT
Measuring malaria progress
 System requirements:
 Areas with low (<5-10%) prevalence cannot affordably use cluster surveys to
measure progress (urban areas and multiple provinces/district)
 NMCC and local authorities (Communities, Districts, Province s) require
greater granularity of measuring progress and targeting interventions
 Zambia has new indicators in HMIS at facility level that reinforce better
information collection routinely



Despite ongoing challenges with timely and complete access to routine
information
Using facilities as sentinels of local level burden via routine reporting
Reinforce training and standard definitions of what should be reported
 Linkage of burden and commodities becoming critical for better targeting
 Must be more efficient with collection and presentation of results for
decision making
 Scalable
STEP 1:Zambia Rapid Reporting system
Solutions
 Reviewed many options
 SMS versus data (GPRS)
 Many branded solutions (SMS for Life, RapidSMS,
EpiSurveyor, etc.)
 Settled on DHIS2 and its Mobile Client
 Internationally recognized
 Established history of development and practice
 Customizable by countries to meet their own needs
 Zambia national HMIS is based on DHIS (1.4)

Easy to roll up existing national datasets
 Access to local developer
 Open source software (inexpensive)
 Extensive documentation available
STEP 1:Zambia Rapid Reporting system
DHIS2 additional leverage
 Because DHIS 1.4 is the basis of current national HMIS
allows direct linkage with existing national datasets in
the same system
 Example:


In addition to rapid malaria reporting system, have also
profiled national datasets ability to generate malaria data
National Malaria HMIS Bulletin (click to view online)
 Tremendous communication potential
STEP 1:Zambia Rapid Reporting system
DHIS2 and Mobile client
 DHIS2 accessible through web
 http://dhis.co.zm/dhis

Userid: ‘demo’; password ‘Demonstration1’
 Enabling standard profiles and reports for both routine
HMIS dataset and Rapid Malaria Report through mobile
client
 Mobile client (Cell phone)
 Runs on low-end phones (Nokia 2330s and 2690s)
 Java-based application with data fields
STEP 1:Zambia Rapid Reporting system
DHIS2 and Mobile client interface
STEP 1:Zambia Rapid Reporting system
Reporting indicators
 Prioritized information already available
 HIA1 (HMIS) routine monthly forms
 Helps create consistency with compiling monthly
reports
 Added commodities (Logistics R&R form)
 Coartem by pack size (dispensed and balance on hand)

(due to problems with cutting packs and lack of information
to inform push and pull with existing forms)
 RDT stocks (tested and balance on hand)
STEP 1:Zambia Rapid Reporting system
Malaria surveillance Indicators
Definitions
Total OPD Attendance
Total outpatient daily attendance for the reporting period, all ages
Clinical malaria cases
Total malaria cases suspected as malaria but not tested
RDT tested cases
Total suspected malaria cases tested with RDTs
RDT positive cases
Total suspected malaria cases tested with RDTs and with a positive
RDT test result
Total suspected malaria cases tested with slide microscopy
Microscopy tested cases
Microscopy positive cases
Positive cases < 5 years
Positive cases ≥ 5 years
Total suspected malaria cases tested with slide microscopy and with
a positive microscopy test result
Total parasitologically-confirmed positive malaria cases under age 5
ACT Stocks: 6s dispensed
Total parasitologically-confirmed positive malaria cases age 5 and
over
Number of ACT treatments dispensed (pack size 6)
ACT Stocks: 6s Balance on hand
Number of ACT treatments packs on hand (pack size 6)
ACT Stocks: 12s dispensed
Number of ACT treatments dispensed (pack size 12)
ACT Stocks: 12s Balance on hand
Number of ACT treatments packs on hand (pack size 12)
ACT Stocks: 18s dispensed
Number of ACT treatments dispensed (pack size 18)
ACT Stocks: 18s Balance on hand
Number of ACT treatments packs on hand (pack size 18)
ACT Stocks: 24s dispensed
Number of ACT treatments dispensed (pack size 24)
ACT Stocks: 24s Balance on hand
Number of ACT treatments packs on hand (pack size 24)
RDT Stocks: RDT Balance on hand
RDT tests kits on hand at facility (stock room plus consultation
rooms)
STEP 1:Zambia Rapid Reporting system
Information discernible
Malaria burden
 Testing rates (by RDT and/or Microscopy)
 Positivity rates (by RDT and/or Microscopy, by age)
 API (testing rate x positivity rate)
 Relative change in malaria against OPD attendance
 Transition in diagnosing clinical versus confirmed
Stock management
 Stock controls relative to burden
STEP 1:Zambia Rapid Reporting system
Progress to date
 Established test server and mobile client January
 3 pilot districts, 3 facilities in each district
 Kazungula, Chibombo, Kaoma
 Initial District Health Information Officer training
(ToT) early February
 Pilot facilities began reporting mid February
 Roll out began in May
 To date 17 districts currently reporting
STEP 1:Zambia Rapid Reporting system
Roll out by March 2011
STEP 1:Zambia Rapid Reporting system
Roll out during 2011
by May
STEP 1:Zambia Rapid Reporting system
Roll out during 2011
by August
STEP 1:Zambia Rapid Reporting system
Planned by 2011
November
STEP 1:Zambia Rapid Reporting system
Opportunities for collaboration
 Important to have similar information in cross-border
districts to inform progress
 Particularly important with elimination zone emerging in
southern Zambia
 DHIS2 hosted solution not necessary to replicate
 Existing DHIS2 server could be used by Senegal, Tanzania,
Namibia, Botswana, Zimbabwe, etc.
 Able to be used across additional disease and reporting
areas within Zambia
 Logistics, notifiable disease, CHWs, etc.
 Existing DHIS Mobile application used in Zambia could be
used by anyone anywhere
STEP 1:Zambia Rapid Reporting system
Thank you.
 This system is being developed with support and input
from a number of partners including Ministry of
Health (NMCC), PATH MACEPA, Akros Research,
WHO, and Malaria Institute at Macha
STEP 1:Zambia Rapid Reporting system