Richard Morter explains the findings of a recent study he was involved in during his rotation project at the KEMRI-Wellcome Trust Research Programme in Kenya.
Malaria is a mosquito-transmitted parasitic infection and although it is treatable if diagnosed early enough, approximately half a million people die each year from malaria. Around 70% of these deaths are in children under the age of five.
Malaria therefore presents a huge burden to global health. Although incidence is reducing globally, there is still a long way to go to reach elimination. The most effective tools currently used to control the spread of malaria are the insecticide-treated bed nets and indoor residual spraying (the application of insecticides to the walls of people’s homes where mosquitos might rest).
Traditionally, malaria control programmes have involved blanket coverage of endemic areas, where every single house in an area is given bed nets or has their houses sprayed. However there is growing interest in adopting more targeted approaches where only those most at-risk are selected for intervention.
The advantage of this is largely economic. The hope would be that targeted intervention in a defined geographic area would yield the same overall reduction in malaria transmission as blanket coverage, but using fewer resources. This would mean more areas could be covered for the same cost leading to a more universal reduction in malaria transmission.
Malaria transmission intensity is inherently uneven across different areas. It’s unevenly spread across the tropical world with sub-Saharan Africa accounting for over 90% of all cases. It’s unevenly spread within Africa too. This unevenness is called spatial heterogeneity of transmission intensity.
In fact; as we zoom in on smaller geographic areas, we continue to see spatial heterogeneity. We can even see it right down at the single homestead level – infected children are not uniformly spread across a village but instead are tightly clustered together, living in either the same or adjacent homesteads. These locations are described as ‘hotspots’ of malaria transmission and could be targeted for control interventions.
Hotspots have been identified by our group in nearby villages along the Kenyan coast, Junju, Ngerenya and Ganze. Junju has moderately high transmission intensity whereas Ngerenya and Ganze have very low transmission intensity.
For targeted interventions to work, hotspots need to be detected accurately. In this paper, we investigated just how accurate current methods are in detecting hotspots.
The first question to ask is; do hotspots remain stable over time? In other words, if we use a previous year’s hotspot data, and direct control interventions to those locations, will the hotspots be in the same place the next year or are we chasing a moving target? In this study, we discovered that the hotspots are indeed stable over time in the high-transmission village, however there appears to be less stability in the lower-transmission villages. What may be required in the future is a more real-time approach where hotspots are detected as they form and immediately targeted.
The second question we addressed is; what method should be used to detect hotspots? We used three different methods to detect parasite infection and subsequently identify hotspots; microscopy, rapid diagnostic testing (RDT) and qPCR.
The gold standard method for malaria diagnosis is microscopy. It’s cheap and already almost universally available in malaria endemic areas, however it lacks sensitivity meaning infections with low numbers of parasites are often not detected.
RDTs work in a similar way to pregnancy tests and a band appears on the test stick if the blood sample contains parasites. They are also relatively cheap and might have slightly better sensitivity to microscopy.
A much newer and more sensitive tool is qPCR where parasite DNA in a blood sample is amplified in an enzymatic reaction. This amplification is detected and indicates a positive sample. qPCR can detect positive samples with much lower parasite counts than microscopy or RDTs, however it’s expensive and requires more specialist equipment.
We compared the abilities of microscopy, RDTs and qPCR to detect hotspots in settings of different transmission intensities and assessed the degree of overlap between hotspots detected by the methods. We found that hotspots were easily detected by all methods in the high transmission setting but microscopy was less reliable in the low transmission setting. The degree of overlap was least for RDTs. Microscopy also became more inconsistent and the hotspots it was detecting overlapped less with qPCR in the low transmission setting.
This is because RDTs and microscopy are less sensitive methods so are less reliable in being able to accurately detect hotspots especially when there are fewer positive samples. Because of this, we suggest that qPCR should preferentially be used particularly as transmission intensity decreases.
Overall, targeted malaria control programmes are an important part of elimination campaigns. Hotspots become more apparent as transmission intensity falls and becomes patchier, therefore hotspot targeting will become even more important in the future as global malaria incidence gradually declines. We found that qPCR becomes more important in this situation. More needs to be done to increase the accessibility of qPCR in malaria-endemic low and middle income countries by reducing cost and simplifying technologies.
Together, these strategies may help contribute to controlling and eventually eliminating malaria worldwide.
The full paper can be accessed at: https://doi.org/10.1093/infdis/jix321
Polycarp Mogeni, Thomas N. Williams, Irene Omedo, Domtila Kimani, Joyce M. Ngoi, Jedida Mwacharo, Richard Morter, Christopher Nyundo, Juliana Wambua, George Nyangweso, Melissa Kapulu, Gregory Fegan, Philip Bejon; Detecting Malaria Hotspots: a comparison between RDT, Microscopy and Polymerase Chain Reaction. J Infect Dis 2017 jix321. doi: 10.1093/infdis/jix321
Author: Richard Morter
Richard is now undertaking a collaborative DPhil project between the Jenner Institute, University of Oxford and the KEMRI-Wellcome Trust Research Programme, supervised by Professors Adrian Hill and Philip Bejon. He is characterising the Regulatory T cell response in a human malaria challenge model and looking at the consequences of malaria-induced Regulatory T cells on effective vaccination against malaria.
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