Dataset Information

Novel approaches to risk stratification to support malaria elimination: an example from Cambodia.

ABSTRACT:

Background

Accurate malaria stratification is essential for effective targeting of interventions but represents a particular challenge in pre-elimination settings. In these settings transmission is typically sufficiently low and spatially heterogeneous to warrant a need for estimates of malaria risk at sub-district or village level but is also likely to be sufficiently high to render the type of decision support systems appropriate to the final stages of malaria elimination impractical. In such a scenario it is arguably more feasible to strengthen existing passive malaria surveillance systems so that routinely generated case data can provide an effective basis for stratifying malaria risk. This paper explores the utility of routine malaria surveillance data for the stratification of malaria risk in Cambodia, where the target is malaria elimination by 2025.

Methods

A malaria information system (MIS) was developed to generate timely, routine data on temporal and spatial variations in malaria cases reported through public health facilities and village malaria workers (VMWs). The MIS was implemented across all malaria endemic districts in the country during 2010-11. In 2012 MIS data were extracted and assessed on the basis of coverage and completeness. Village-level incidence estimates for 2011 were generated using predefined data inclusion criteria.

Results

In 2011, the MIS covered 681 health facilities and 1,489 VMW villages; the overall completeness of monthly reporting was 82& and 97& for health facilities and VMWs respectively. Using these data it was possible to estimate malaria incidence for 89& of villages covered by the MIS. The resulting stratification highlights the highly heterogeneous nature of malaria transmission in Cambodia and underlines the importance of village-level data for effective targeting of interventions, including VMWs. Challenges associated with implementing the MIS and the implications of these for developing viable and sustainable MIS in Cambodia and elsewhere are discussed.

Conclusions

This study demonstrates the operational feasibility of introducing a system to routinely generate village level malaria case data in Cambodia. Although resulting incidence estimates are subject to various limitations and biases the data provide an objective, repeatable basis for a dynamic system of stratification which is appropriate for guiding the transition between malaria pre-elimination and elimination phases.

SUBMITTER: Cox J

PROVIDER: S-EPMC4177243 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Novel approaches to risk stratification to support malaria elimination: an example from Cambodia.

Cox Jonathan J Sovannaroth Siv S Dy Soley Lek L Ngor Pengby P Mellor Steven S Roca-Feltrer Arantxa A

Malaria journal 20140919

<h4>Background</h4>Accurate malaria stratification is essential for effective targeting of interventions but represents a particular challenge in pre-elimination settings. In these settings transmission is typically sufficiently low and spatially heterogeneous to warrant a need for estimates of malaria risk at sub-district or village level but is also likely to be sufficiently high to render the type of decision support systems appropriate to the final stages of malaria elimination impractical. ...[more]

PMID: 25233886

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Project description:BackgroundMalaria in Cambodia has decreased by 90.8% between 2010 and 2020, driven by the commitment of the National Center for Parasitology, Entomology and Malaria (CNM) and the achievements of the roll-out of a village malaria worker programme. However, in the first seven months of 2018, CNM identified a 207% increase (11,969 to 36,778) in confirmed malaria cases compared to the same months in the previous year. To address this increase, CNM developed the "Intensification Plan" (IP), implemented between October 2018 and December 2020.MethodsThe structure of the IP was summarized, including the selection of sites, the interventions implemented in the selected health facility catchment areas (HFCAs) and the monitoring and evaluation process. Data on IP interventions were collected by CNM and civil society organisations. Data on malaria cases and tests from all HFCAs in Cambodia from January 2018 to December 2020 were sourced from the Cambodia Malaria Information System (MIS) and WHO Malaria Elimination Database. Malaria data from IP HFCAs and non-IP HFCAs was analysed and compared to present the changes in malaria testing and confirmed cases before and during implementation of the IP.ResultsBetween October 2018 and December 2020, through the IP 16,902 forest packs and 293,090 long-lasting insecticide treated nets were distributed. In the 45 HFCAs included in the IP, 431,143 malaria tests were performed and 29,819 malaria cases were diagnosed, 5364 (18%) of which were Plasmodium falciparum/mixed cases. During the intervention period, over all HFCAs included in IP, P. falciparum/mixed cases declined from 1029 to 39, a 96.2% decrease, and from 25.4 P. falciparum/mixed cases per HFCA to 0.9. HFCAs not included in IP declined from 468 to 43 cases, a 90.8% decrease, showing that routine malaria activities in Cambodia were also playing an important contribution to malaria control.ConclusionsOver the course of IP implementation there was a substantial increase in malaria testing and both overall malaria cases and P. falciparum/mixed cases decreased month on month. The initiative yields lessons learned for Cambodia to reach the final stage of elimination as well as for other countries aiming to accelerate their malaria control programmes.

Project description:BackgroundMalaria elimination requires a variety of approaches individually optimized for different transmission settings. A recent field study in an area of low seasonal transmission in South West Cambodia demonstrated dramatic reductions in malaria parasite prevalence following both mass drug administration (MDA) and high treatment coverage of symptomatic patients with artemisinin-piperaquine plus primaquine. This study employed multiple combined strategies and it was unclear what contribution each made to the reductions in malaria.Method and findingsA mathematical model fitted to the trial results was used to assess the effects of the various components of these interventions, design optimal elimination strategies, and explore their interactions with artemisinin resistance, which has recently been discovered in Western Cambodia. The modelling indicated that most of the initial reduction of P. falciparum malaria resulted from MDA with artemisinin-piperaquine. The subsequent continued decline and near elimination resulted mainly from high coverage with artemisinin-piperaquine treatment. Both these strategies were more effective with the addition of primaquine. MDA with artemisinin combination therapy (ACT) increased the proportion of artemisinin resistant infections, although much less than treatment of symptomatic cases with ACT, and this increase was slowed by adding primaquine. Artemisinin resistance reduced the effectiveness of interventions using ACT when the prevalence of resistance was very high. The main results were robust to assumptions about primaquine action, and immunity.ConclusionsThe key messages of these modelling results for policy makers were: high coverage with ACT treatment can produce a long-term reduction in malaria whereas the impact of MDA is generally only short-term; primaquine enhances the effect of ACT in eliminating malaria and reduces the increase in proportion of artemisinin resistant infections; parasite prevalence is a better surveillance measure for elimination programmes than numbers of symptomatic cases; combinations of interventions are most effective and sustained efforts are crucial for successful elimination.

Dataset Information

Novel approaches to risk stratification to support malaria elimination: an example from Cambodia.

Background

Methods

Results

Conclusions

Publications

Novel approaches to risk stratification to support malaria elimination: an example from Cambodia.

Similar Datasets

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