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Spectacular decline of malaria on Malaita: A review of laboratory-based data Helen Polosovai BApplSc(MedLab) AAH Laboratory Dept.

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Presentation on theme: "Spectacular decline of malaria on Malaita: A review of laboratory-based data Helen Polosovai BApplSc(MedLab) AAH Laboratory Dept."— Presentation transcript:

1 Spectacular decline of malaria on Malaita: A review of laboratory-based data Helen Polosovai BApplSc(MedLab) AAH Laboratory Dept

2 Published in Western Pacific Surveillance and Response Journal 2014,5(3):1-10

3 Background.  In the 22 Pacific Island Countries and Territories, malaria is endemic in Papua New Guinea, Solomon Islands and Vanuatu.  Solomon Islands has been successful in reducing malaria incidence and mortality.  In Malaita Province, the annual parasite index (API) was 137 in 1996, 83 in 2009 and 33.5 in 2011.  API = number of positive slides per 1000 population per year.

4 Aims of the study AAH laboratory noted a decline in the number of malaria cases and the proportion of cases due to Plasmoduim falciparum (Pf). The aims of this study were to use the data from malaria tests performed at AAH from 2008 to 2013 to: (1) describe the trend in confirmed malaria and the proportion of Pf to Plasmodium vivax (Pv); (2) confirm any trends in the laboratory data by assessment of malaria treatment and admission data; (3) determine the API for the AAH catchment area and for major villages in this area for 2008 and 2013.

5 Methods Descriptive study involving review of (1) laboratory records of malaria tests; (2) admissions for malaria; and (3) prescription of malaria treatments. Details recorded for every malaria test: date of test, patient name, age, sex, village and results. All malaria tests were thick blood films stained with Romanovsky stain. Additional data on malaria cases extracted from Admission register and OPD treatment records. All records from 2008 to 2013 were entered into Excel and analyzed.

6 Results From 2008 to 2013, the AAH examined 35,608 blood films for malaria. The annual number of tests decreased 45.2% over this period. The number of cases of malaria and percent positive were highest in 2008 (1817 and 23.6%) and lowest in 2013 (246 and 5.8%) Between 2008 and 2013 the total number of positive cases of malaria decreased by 86.5%, Pf by 96.7% and Pv by 65.3%. The ratio of Pf to Pv reversed in 2010 from 2.059 in 2008 to 0.194 in 2013.

7 Malaria decreased by 86.5%

8 Ratio of Pf/Pv reversed

9 Number of malaria cases by species and month for 2008 & 2013, demonstrating marked decline in both species and development of a seasonal pattern for Plasmodium falciparum in 2013

10 Admissions and deaths The annual number of admissions declined 90.8% from 2008 to 2013 and the number of deaths fell to zero.

11 Malaria treatment The number of malaria treatment fell 91% from 2008 to 2013. Chloroquine, Fansidar and quinine were not used after 2009. CoArtem was used from July 2009.

12 Malaria incidence in villages The API for the Atoifi catchment area declined from 195 in 2008 to 24 in 2013. We were able to calculate API for large villages. API decreased for all villages. Some villages API remain high (eg, Gounasu’u, Abitona & Wyfolonga) in 2013 while others API were low.(eg, Gethsemane, Sifilo, Alasi)

13 Gethsemane Alasi Sifilo Gounsu’u Ambitona Atoifi Hospital catchment Atoifi Hospital Wyfolonga

14 Discussion The data show a remarkable fall in the number of blood films positive for malaria, particularly for Pf. The fall in the number of Pf cases was so great that in 2013, no cases were diagnosed in four months and a pattern consistent with seasonal transmission appeared for the first time. The seasonal pattern has been maintained in 2014 (Pf/Pv 9/203) and 2015 (Pf/Pv 1/48 Jan & Feb)

15 Conclusion The decline in malaria cases in the AAH catchment area has been spectacular, particularly for Pf. This was supported by three sources of hospital surveillance data (laboratory, admissions and treatment records). The decline was associated with the use of artemisinin- based combined therapy and improved vertical social capital between the AAH and the local communities. Calculating village-specific API has highlighted which villages need to be targeted by the AAH malaria control team.

16 New questions arise  If malaria causes only 6% of fever, what are the causes of the other 94%?  AAH needs improved laboratory diagnostic capacity.  Why do some villages still have a high incidence of malaria?  How can this be reduced?


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