A TPP serves as a benchmark by which to compare technological platforms and analysis methods against each other. The TPP and methods comparison steps indicate which platforms should be used for pilot testing in real-world programmatic settings. Program test cases ultimately inform the establishment of normative policy guidance for global implementation. To begin, a review was conducted of literature regarding genetic epidemiology and malaria elimination strategies.
Molecular genetic epidemiology: a laboratory perspective
The literature review engaged an exploratory search strategy in both published and grey literature databases such as the MESA research hub [ 10 ], starting with key search terms, and allowing those findings to inform the next cycle of search terms and contacts in a cascade search. Initial search terms included malaria transmission, genetic epidemiology, genetic sequencing, and population genetics.
To inform and complement the literature review, between March and September , individual in-depth interviews were conducted with 15 international stakeholders identified through the review—including malaria disease experts, laboratory and field researchers, programme implementers, mathematical modellers, policymakers, and donors for their input as to the needs and opportunities for genetic information in malaria elimination.
The development of the list of use cases was informed by the critical review of the literature and informational interviews with experts. These two pillars comprise activities for which genetic epidemiology applications have the most promising applications: surveillance, case investigation, and stratification of areas for targeted interventions to reduce transmission and accelerate elimination. Activities falling outside the WHO framework, for example using genetic techniques to guide product development such as rapid diagnostic tests RDTs , were considered out of scope.
This use case framework is modeled on an early draft of use cases developed by a working group of soil-transmitted helminths diagnostic experts published last year [ 8 ]. Finally, the categorization and content of the use cases was iteratively developed and revised by sharing drafts with previously interviewed experts. Seven use cases are presented where genetic epidemiology approaches are informative to decision-making within the efforts of NMCPs.
The use cases are intended to be technology-agnostic such that they may be generalizable across many endemic settings with different epidemiological characteristics e. Use cases are designed to align multiple scientific fields related to malaria control and eradication under a singular goal, incorporating research and programme perspectives. The structure of a use case delineates the conditions under which the method or tool would be applicable and useful.
The content of each use case, presented here, is organized into three components: description, pre-conditions, and post-conditions. The description section conveys, briefly, the objective sought by use of the method—what information the genetic epidemiology method is providing—as well as the current method used to achieve that objective in the absence of a genetic method.
Pre-conditions describe the type of case detection active, passive, or reactive , prevalence of infection high, moderate, low, and very low , and focus type active, residual non-active, and cleared. These categorizations of epidemiological characteristics are all aligned to those used in the WHO Framework for Elimination and use the same definition.
Sampling frame representative or dense is also listed as a pre-condition to depict the degree to which the target population needs to be sampled for a genetic method to be informative. Finally, the population level of implementation e. These vary across use cases and serve to provide an orientation to the objectives.
Post-conditions focus on the consumers of information and depict how the data will be identified, utilized, and presented. This includes the potential actions informed by the results of the genetic method, presentation of that output, and the ideal timeframe between sample collection and delivery of data analysis on which the information would be available from the method in order to be informative to programmatic decision-making. For some of the use cases described here, genetic methods have been applied in a malaria control or elimination setting and described in the literature Use cases 1, 2, and 6 ; methods for other use cases have not yet been applied programmatically Use cases 3, 4, 5, and 7.
These use cases are designed to align the efforts of multiple scientific fields towards the shared goal of malaria elimination, incorporating both research and programme perspectives. The content of each use case presents the conditions under which the method or tool is applicable and how it is useful. This use case describes a method that identifies drug resistant parasites within an individual with high sensitivity and specificity, regardless of the presence of symptoms or treatment failure, in a high to very low prevalence setting. Treatment efficacy surveys are currently used to assess population drug resistance but are time-consuming, costly, and may occur with insufficient frequency to inform decision-making.
At a population level, these methods, compared to traditional methods, would serve to estimate resistance prevalence more accurately in a country and accelerate the identification of population trends in the emergence of resistance. Numerous genotyping methods have been developed for detecting particular genetic markers in individual patient samples; nested and real-time polymerase chain reaction PCR are used widely in a variety of country settings.
Molecular Genetic Epidemiology — A Laboratory Perspective | SpringerLink
Other newer methods still in development include: point-of-care resistance testing with loop-mediated isothermal amplification [ 13 , 14 ] and next generation sequencing NGS of single nucleotide polymorphism SNPs [ 15 ]. Each approach has advantages and limitations described in the literature [ 16 , 17 , 18 , 19 , 20 ]. The method depicted in this use case provides information about how resistance genes are spreading in a population of parasites in a setting with high to very low prevalence.
The information provided by the use case enables identification of linked populations and predictive modelling of drug-based interventions. Methods for population genetic analysis have been employed to understand the interaction between gene flow and patterns of resistant marker prevalence in several geographies including Ethiopia [ 21 ] and Cambodia [ 22 ], as well as the dispersal of resistance haplotypes in Eastern Africa and the Democratic Republic of Congo [ 23 ]. NGS technologies are also emerging as a tool for drug resistance surveillance [ 24 ].
This use case is linked to the method described by Use case 1, as it would require aggregation of information collected by Use case 1, along with additional analysis to predict emergence or dissemination of drug resistance into new areas. Application of this use case is most applicable at a regional rather than national level in settings where national malaria programmes interact, such as the Asia Pacific Malaria Elimination Network.
This use case describes a method that allows decision-makers to stratify regions according to transmission intensity in low and very low prevalence settings and monitor the effect of interventions. While current methods use surveys and weekly case counts to measure changes in prevalence and incidence, they are unable to measure genetic signatures indicative of changes in transmission intensity at low prevalence levels, such as changes in parasite population structure. For example, stagnation or increasing case counts might suggest an intervention is failing, even though the resurgence could be due to rising transmission rates from a source not exposed to the intervention.
SNP barcodes have been used to define transmission patterns in populations in many countries, including Senegal [ 25 ], Malawi [ 26 ], Zambia [ 27 ], Cambodia [ 28 ], Panama [ 29 ], and through longitudinal tracking in Papua New Guinea [ 30 ]. Additional investigation is needed to advance and validate methods for the translation of parasite genetic diversity into a measurement of parasite transmission.
This use case defines a method that enables the identification and stratification of foci according to receptivity and transmission intensity, as recommended by WHO guidelines, in moderate to very low prevalence settings [ 12 ]. Specifically, the method measures how closely related parasites are to each other and estimates transmissibility of parasites within different groups. Currently, foci may be inferred using evidence from geospatial surveillance and case investigations, but only a genetic method can definitively link cases based on parasite genetic relatedness and therefore validate current methods for foci identification [ 31 ].
A method for identifying foci, especially in very low transmission settings, is likely to be linked to the method described by Use case 3 because transmission intensity is a characteristic used in foci stratification. In two examples, SNP-genotyping analysis generated by PCR-based assays was used to characterize the Makira region of Madagascar as a hotspot [ 32 ] and assays of microsatellites were used to attribute the resurgence of Plasmodium vivax malaria in Greece to specific villages with foci reactivated by imported malaria via migrant agricultural workers [ 33 ].
However, it is unclear what conditions and geographic scale are necessary to enable the identification of transmission foci that are stable over time using genetic surveillance.
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The method described in this use case determines how parasite populations are linked across various geographic regions with high to very low prevalence and enables a quantitative assessment of how much of transmission in one region is due to contributions from transmission in another. The method is related to the method presented in Use case 2, though without the specificity of anti-malarial resistance.
Therefore, the two use cases may engage similar methods of measurement and analysis and are both relevant at a regional level. Estimates of how parasite populations are linked geospatially may be approximated from human migration data [ 34 ], but this use case proposes a method with higher spatiotemporal resolution. Gene flow has been characterized by a range of analytic techniques using SNP genotype data from nested PCR in Papua New Guinea [ 35 ] and at the Thai-Myanmar border [ 36 ], and genome-wide sequencing in Mauritania, among other countries [ 37 ].
Nucleic Acid-based Diagnosis and Epidemiology of Infectious Diseases
However, these methods vary in their resolution to assert connectivity and additional evidence is needed to validate the associations between genetic patterns of population structure and human migration. An estimate of parasite population connectivity is an essential parameter for epidemiological models of malaria, which may be useful for optimizing elimination strategies [ 38 ].
This use case describes a method for discriminating between indigenous and imported cases in areas with low or zero prevalence by measuring how similar a parasite is to a population of parasites currently or previously endemic to a geographically relevant area. In countries at or approaching zero cases, the method described in this use case provides a more definitive determination than can be offered through the use of travel surveys and case investigations.
Several genetic methods have been demonstrated for this use cases in the literature, especially in countries at or approaching elimination that need to confirm whether a reported case or cluster of cases is due to local transmission or importation in order to maintain their elimination progress. Two high profile examples of such a method in use include: a cluster of cases in Puerto Rico confirmed to be imported from the Dominican Republic [ 39 ] and an outbreak of Plasmodium falciparum malaria among United Nations peacekeeping soldiers in Guatemala that was attributed to exposure when they were stationed in the Democratic Republic of Congo [ 40 ].
Optimization of these methods will be required to generate information useful in real-time scenarios. The method described by this use case will be linked to the one proposed in Use case 6, but with higher resolution to distinguish the contribution of specific sources to ongoing or recurring transmission in an area with low to very low prevalence. The method will provide a high-resolution snapshot of how cases are related to each other—a result definitively attainable only through a genetic method.
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Additionally, the method will need to incorporate both epidemiological and genetic information, as well as complex modeling methods to provide a snapshot of what is contributing to ongoing transmission. This use case is the most abstract in its conceptualization because methods for this purpose are mostly theoretical or have been modeled in specific research contexts [ 41 ]. Furthermore, a method for this use case will require a well characterized parasite population historical and dense surveillance sampling for the method to be applicable in that region.
Few, if any, malaria endemic countries in the world have sufficiently historical and consistent genetic surveillance of their local parasite populations to contextualize a method for this use case. The use cases presented in this article represent a novel application of a common business technique, applied elsewhere in fields of public health and software, and here to address the research-implementation gap in malaria.
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They have already been used to guide discussions at two international meetings focusing on the interactions between NMCP representatives and genome scientists, hosted by the Harvard T. Successful development and implementation of genetic epidemiological methods, through the steps depicted in Fig. This will be especially important in the translation of these use cases into the technical specifications needed for Target Product Profile TPPs that are directly responsive to specific NMCP information needs, including specific endemic settings and parasite-species specific requirements.
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