Using Hawkes Processes to model imported and local malaria cases in near-elimination settings

Modeling malaria transmission in Nepal: impact of imported cases through cross-border mobility

The cross-border mobility of malaria cases poses an obstacle to malaria elimination programmes in many countries, including Nepal. Here, we develop a novel mathematical model to study how the imported malaria cases through the Nepal-India open-border affect the Nepal government's goal of eliminating malaria by 2026. Mathematical analyses and numerical simulations of our model, validated by malaria case data from Nepal, indicate that eliminating malaria from Nepal is possible if strategies promoting the absence of cross-border mobility, complete protection of transmission abroad, or strict border screening and isolation are implemented. For each strategy, we establish the conditions for the elimination of malaria. We further use our model to identify the control strategies that can help maintain a low endemic level. Our results show that the ideal control strategies should be designed according to the average mosquito biting rates that may depend on the location and season.

Is there evidence of sustained human-mosquito-human transmission of the zoonotic malaria Plasmodium knowlesi? A systematic literature review

Background

The zoonotic malaria parasite Plasmodium knowlesi has emerged across Southeast Asia and is now the main cause of malaria in humans in Malaysia. A critical priority for P. knowlesi surveillance and control is understanding whether transmission is entirely zoonotic or is also occurring through human-mosquito-human transmission.

Methods

A systematic literature review was performed to evaluate existing evidence which refutes or supports the occurrence of sustained human-mosquito-human transmission of P. knowlesi. Possible evidence categories and study types which would support or refute non-zoonotic transmission were identified and ranked. A literature search was conducted on Medline, EMBASE and Web of Science using a broad search strategy to identify any possible published literature. Results were synthesized using the Synthesis Without Meta-analysis (SWiM) framework, using vote counting to combine the evidence within specific categories.

Results

Of an initial 7,299 studies screened, 131 studies were included within this review: 87 studies of P. knowlesi prevalence in humans, 14 studies in non-human primates, 13 studies in mosquitoes, and 29 studies with direct evidence refuting or supporting non-zoonotic transmission. Overall, the evidence showed that human-mosquito-human transmission is biologically possible, but there is limited evidence of widespread occurrence in endemic areas. Specific areas of research were identified that require further attention, notably quantitative analyses of potential transmission dynamics, epidemiological and entomological surveys, and ecological studies into the sylvatic cycle of the disease.

Conclusion

There are key questions about P. knowlesi that remain within the areas of research that require more attention. These questions have significant implications for malaria elimination and eradication programs. This paper considers limited but varied research and provides a methodological framework for assessing the likelihood of different transmission patterns for emerging zoonotic diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04110-z.

Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics

Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, genetic distance or accessibility matrices) with temporal information into a single inference framework to infer malaria reproduction numbers. Twelve scenarios were defined, representing different assumptions about the likelihood of transmission occurring over different geographic distances and likelihood of missing infections (as well as high and low amounts of uncertainty in this estimate). These scenarios were applied to four individual level datasets from malaria eliminating contexts to estimate individual reproduction numbers and how they varied over space and time. Model comparison suggested that including spatial information improved models as measured by second order AIC (ΔAICc), compared to time only results. Across scenarios and across datasets, including spatial information tended to increase the seasonality of temporal patterns in reproduction numbers and reduced noise in the temporal distribution of reproduction numbers. The best performing parameterisations assumed long-range transmission (> 200 km) was possible. Our approach is flexible and provides the potential to incorporate other sources of information which can be converted into distance or adjacency matrices such as travel times or molecular markers.