Using information technology for resistance containment: Malaria surveillance in the future moving toward elimination strategy By Wichai Satimai MD.,MA.,DTM&H Bureau of Vector Borne diseases Department of Disease Control Ministry of Public Health Thailand
Annual Blood Examination Rate (ABER), Slide PositivityRate (SPR) and Annual Parasite Incidence (API/1,000), Thailand FY 1965-2011 ABER & SPR / 100 pop. 16 14 12 10 8 6 4 2 0 ABER SPR API API / 1,000 pop. 16 14 12 10 8 6 4 2.18 2 1.11 0.24 0 Fiscal Year
Percentage Proportion of malaria parasite species, Thailand, FY 1965-2011 100 80 P. falciparum 60 40 60.8 38.2 20 P. vivax 0 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 Fiscal Year P.falciparum P.vivax
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Proportion of malaria parasite species in relation to the National drug policy, Thailand, FY 1965-2010 Percentage 100 CHL SP2 SP3 QT MSP M M 80 60 1965 CHL 1973 SP 1982 1985 QT MSP 1990 M 1995 M+ATS ; only in Trat, Chantaburi, Tak 40 20 2005 M+ATS whole country in 2005 (2days) 2008 M+ATS 3 days 0 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 Fiscal Year P.falciparum P.vivax
1 2 Nine Provinces as Sentinel sites for monitoring of drug resistance 1.Mae Hong Son 3 4 7 8 6 2.Tak 3.Kanchanaburi 4.Ratchaburi 5.Ranong 5 6.Ubon Ratchathania 9 7.Chanthaburi 8.Trat 7
Tak Mef 25 mg/kg + Art 12 mg/kg for 2 days N ACPR% LTF% ETF% 1997: 38 89.5 10.5 0 2002: 39 92.3 5.4 2.6 2003: 71 96.6 3.4 0 2004: 47 86.5 13.5 0 2006: 46 89 11 0 1997 2002 2003 2004 2006
MHS CHM 2003 TR UB TAK 1997 2002 2003 2004 1997 1997 1998 1998 KB 1997 2002 2003 2004 2005 2006 2002 1999 RB 1997 2002 2002 2003 2004 CHB 2003 2002 2002 RN 2003 2002 2004 2005 2006 2004 2003 2003 1997 M3 1998 2000 2005 2002 2003 2004 M3A12 M5A12 2004 2006 2004
Result 3: Efficacy of CQ, 2009-2010 MH CB YL KN No. recruited 56 55 53 48 Lost 6 5 0 0 Withdrawn) 2 0 0 0 No. analyzed 48 50 53 48 % Parasitaemia 8.3 30 0 31.3 Day 3 % ACPR 100 96 100 93.8 % ETF 0 0 0 0 % LCF 0 0 0 0 % LPF 0 4 0 6.2
11 Implementation Areas Ubonratchathani Srisaket Surin Burirum Sakaeo Only Zone 1 areas use Atovaquone/Proguanil The rest follows the national drug policy Chanthaburi Trat Zone 1
Table 2 Primer pairs and specific restriction enzymes for detecting 3 polymorphisms at codon 268 Primer pairs and specific restriction enzymes for detecting 3 polymorphisms Codon 268 Type Primer pair Restriction Enzyme DNA Sequencing Outer primer Product size (base pair) CYTB1+CYTB2 939 TAT Wild type CYTB3+CYTB5 NsiI 359+25 TCT Y268S CYTB2+CYTB6 AlwNI 147+24 AAT Y268N CYTB2+CYTB7 SspI 150+24 NsiI cuts TAT; AlwNI cuts TCT; SspI cuts TAT and TCT, but not AAT
Web-based malaria surveillance: Malaria surveillance in the future moving toward malaria elimination in Thailand
Original System: Forms are recorded, and summarized on paper
Detected cases are plotted on household walking map
Objective To provide effective management information system capable of coordination at operational staff to enable rapid and high quality implementation of malaria elimination strategy
3 out of 6 Core Modules in Vector-Borne Disease Control have been implemented Epidemiology Module Vector Control Module BCC Module
Key Features Case Management (Real time Village V.S. household level traceable) Case detection Case Investigation Case Follow up Vector Control (Effectively distributed/controlled) The most up-to-date population survey cover any risk areas LLIN /LLIHN distribution IRS action Impregnated Bed Net Distribution Behavioral Change Communication (Individual Home Visit information can be sent to the center for evaluating the awareness of residences within the target areas) Different type of reports displayed in different presentation format (table, graph,gis,etc.) Integrate into public heath routine tasks Simple and easy to interpret, and user friendly
Technologies Web-based synchronization technology capable of switching between offline / online mode of data entry. This terminology is benefit for the low resources area. Users can still operate in case of internet link has difficulties. Then data can be later transferred when internet is back to normal. Mobile Computing simply disseminated or received information to/from different devices in other platforms i.e. Mobile/ Tablet Geographical Information System (GIS) ready ability to toggle GIS in key element of indicators for better understanding of the situation in short term
Work & Data Flow MIS EP 1 FU EP 1 VIVO Not Infected Infected Case Detection EP 1 EP 3 Case investigation Treatment Day 0 Drug compliance Case follow-up Day 1,2,3 Case follow-up Pf : Day 7,14,21,28,35,42 Pv: Day 7,14,21,28,60,90
Data Capturing for Case Management Active Case/Passive Case Detection Location Information Diagnosis Treatment
Infected Cases Follow Up Schedule generated automatically
Cases Follow Up can be done through Tablet 7 inches Device
Epidemiology Summary Report
Epidemiology Reports can be displayed in different format (Table, Bar Chart, Pie, or Line), and different time frame (monthly, Weekly)
Day 0 alert will be sent using SMS on a daily basis and Summary on a weekly basis
Maps in Malaria GIS (http://gis.biophics.org) 1. Number of Malaria Cases 2. Malaria Incidence 3. Proportion of PF Malaria Receiving ACT 4. Proportion of PV Malaria Receiving chloroquine and primaquine 5. Percent of PF Malaria Receiving ACT and have DOT 6. Percent of PF Malaria Receiving ACT, DOT but Day 3 Positive 7. PF Cases Receiving ACT, DOT but Day 3 Positive (by Patient) 8. Percent of malaria cases who got investigate 9. Indigenous Case 10. Malaria Stratification Area
GIS can display number of Malaria Cases classified by administrative level up to village level
Cases Investigation captured cases which have possible same source of infection March 18, 2010
Day 3 Positive Cases (ACT) 2009-2012 2010 2011 2012=81 2009 = 14 33 54 cases Cases cases
Conclusions New technology can become one of a major strategy to fight against Vector-Borne Disease Knowledge sharing/transferring should be strengthened among regional countries in order to exchange information across different territories Regional and Global Collaborations or networking across public health units should be initialized for the purpose of joining/sharing disease control tasks, and lead to practical integration between working units across barriers
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