INTRODUCTION
Characterising pathogen transmission dynamics using population genomics is essential to guide containment efforts and to plan strategies for disease elimination (Grad & Lipsitch, 2014; Hedtke et al., 2019; Wlodarska, Johnston, Gardy, & Tang, 2015). Pathogen populations comprise genetically distinct individuals that are related to varying degrees due to the accumulation of genetic variation as they transmit from host to host. Genomic diversity within populations can thereby indicate the extent of transmission intensity, whilst that between populations determines their connectivity (gene flow) and is influenced by local selection and inbreeding. Measuring pairwise relationships between infections further identifies how infections are spreading from host to host within a population and allows epidemiological characteristics of transmission to be defined (e.g. endemic versus epidemic). Understanding how these population genetic parameters change under the pressure of control interventions is central to using genomic epidemiology as an effective tool to monitor pathogen transmission dynamics.
When utilising population genetics to measure transmission dynamics it is important to consider how genomic diversity is generated. Human malaria parasites acquire de novo mutations whilst replicating asexually and reassortment occurs through sexual recombination within the mosquito vector. However, the generation of novel recombinants occurs only if the mosquito has taken up multiple, genetically distinct clones in the blood meal, otherwise self-fertilization occurs, and progeny are clonal. Outcrossing is therefore dependent on the presence of multiple genetically distinct infections in the human host and increases with endemicity (Babiker et al., 1994; Paul et al., 1995). The population structure of the most virulent malaria parasite,Plasmodium falciparum is associated with transmission intensity (Anderson et al., 2000). At moderate to high transmission where multiclonal infections are frequently found, parasite populations are characterised by high diversity and a lack of population structure with low levels of linkage disequilibrium (LD) (Anderson et al., 2000; Gatei et al., 2010; Orjuela-Sanchez et al., 2013; Salgueiro, Vicente, Figueiredo, & Pinto, 2016; Schultz et al., 2010). At low transmission where multiclonal infections are less common, clonal transmission and inbreeding amongst closely related individuals is more common, resulting in lower overall diversity and high levels of LD, whilst population structure is more evident due to both lower gene flow between areas and within population transmission dynamics (Anderson et al., 2000; Branch et al., 2011; Chenet, Schneider, Villegas, & Escalante, 2012; Noviyanti et al., 2015). For P. vivax , also a significant human pathogen, relapsing infections and other unique features that enhance its transmission (Olliaro et al., 2016), result in a higher prevalence of multiclonal infections. Therefore, P. vivax populations are often characterised by high genetic diversity, even at low transmission (Ferreira et al., 2007; Fola et al., 2017; Gunawardena, Ferreira, Kapilananda, Wirth, & Karunaweera, 2014; Noviyanti et al., 2015; Waltmann et al., 2018). In the South West Pacific region, a modest decline in diversity and increasing population structure occurs with the eastward decline in transmission (Fola et al., 2017; Koepfli et al., 2013; Waltmann et al., 2018). LD and pockets of clonal P. vivaxtransmission have been observed in several studies, suggesting increasingly focal transmission as malaria rates decline (Abdullah et al., 2013; Batista, Barbosa, Da Silva Bastos, Viana, & Ferreira, 2015; Chenet et al., 2012; Delgado-Ratto et al., 2016; Ferreira et al., 2007; Imwong et al., 2007; Iwagami et al., 2012; Noviyanti et al., 2015; Orjuela-Sanchez et al., 2013). Comparative analyses show P. vivaxhas a higher effective transmission intensity (Hofmann et al., 2017; Lin et al., 2010; Robinson et al., 2015) and higher diversity than P. falciparum due to a longer association with humans and fewer population bottlenecks (Chenet et al., 2012; Gilabert et al., 2018; Hupalo et al., 2016; Jennison et al., 2015; Liu et al., 2014; Loy et al., 2017; Neafsey et al., 2012; Noviyanti et al., 2015; Orjuela-Sanchez et al., 2013; Pava et al., 2017). P. vivax is more resilient to control efforts and thus may be less likely to show changes in parasite population structure than P. falciparum (Barry, Waltmann, Koepfli, Barnadas, & Mueller, 2015; Cornejo & Escalante, 2006; Feachem et al., 2010; Liu et al., 2014; Neafsey et al., 2012; Oliveira-Ferreira et al., 2010; Waltmann et al., 2015). No studies have yet investigated the impact of intensified control on the population genetics of sympatric P. vivax and P. falciparum populations.
The worldwide scale up of malaria control since the early 2000s, has reduced transmission dramatically around the world. Indeed, between 2010 and 2016, disease incidence declined by 18% and mortality by 32% (WHO, 2017, 2019). The incidence of clinical cases and infection prevalence remain the mainstay of malaria surveillance however population genetic surveillance has emerged as a promising and high-resolution approach for malaria monitoring (Arnott, Barry, & Reeder, 2012; Barry et al., 2015; Dalmat, Naughton, Kwan-Gett, Slyker, & Stuckey, 2019; Koepfli & Mueller, 2017; malEra Consultative Group on Monitoring & Surveillance, 2011). Specifically, these approaches identify local transmission dynamics (e.g. endemic, epidemic, imported infections), connectivity between parasite populations in different endemic areas (Anderson et al., 2000; Fola et al., 2017; Noviyanti et al., 2015; Vardo-Zalik et al., 2013; Waltmann et al., 2018) and “sources and sinks”, which together could help to design targeted control interventions (Auburn & Barry, 2017; Barry et al., 2015; Koepfli & Mueller, 2017). Population genetic surveys could also identify local drivers contributing to sustained transmission such as particular human social and economic interactions (Barry et al., 2015; Delgado-Ratto et al., 2016; Koepfli & Mueller, 2017). While parasite population genetics and genomics is becoming more popular and accessible, the impact on control programs has been limited, and to date few studies have systematically assessed the long-term impact of malaria control using these approaches (Bei et al., 2018; Chenet, Taylor, Blair, Zuluaga, & Escalante, 2015; R. F. Daniels et al., 2015; Gatei et al., 2010; Gunawardena et al., 2014; Nkhoma et al., 2013; Vardo-Zalik et al., 2013). Moreover, it is not clear how long transmission needs to be disrupted, or to which extent prevalence should be reduced, before changes in parasite population structure can be seen. A better understanding of the impact of malaria control interventions onP. falciparum and P. vivax population structure is urgently required to capitalise on the potential of genomic surveillance for malaria control and elimination.
Population genetic surveys using panels of well-validated neutral microsatellite markers (Anderson et al., 2000; Imwong et al., 2007; Karunaweera, Ferreira, Hartl, & Wirth, 2006) were conducted on the north coast of Papua New Guinea before the intensification of malaria control (2005/2006). P. vivax showed higher genetic diversity and a lack of population structure yet there was significant population structure of P. falciparum populations (Jennison et al., 2015; Koepfli et al., 2013; Schultz et al., 2010; Waltmann et al., 2018). Significant inbreeding (mLD) was not observed for sub-populations of either species, confirming high levels of outcrossing and endemic transmission (Jennison et al., 2015). Since that time, PNG has implemented an intensified control program including the free nationwide distribution of Long Lasting Insecticide Treated Nets (LLIN). This resulted in a significant decline in infections across the country including the north coast provinces previously covered in our population genetic surveys (Arnott et al., 2013; Barry et al., 2013; Hetzel et al., 2016; Kattenberg et al., 2020; Koepfli et al., 2017; Koepfli et al., 2015). The impact on parasite population structure and transmission dynamics after the rollout of LLINs, however, remains unresolved. We sought to characterise impact of reduced prevalence on the population structure of sympatric P. falciparum and P. vivaxpopulations. Microsatellite haplotypes were generated from P. falciparum and P. vivax samples collected in multiple cross sectional surveys from 2010-14 after two rounds of mass LLIN distribution and compared to published data from isolates collected before the intensified malaria control program (Jennison et al., 2015; Schultz et al., 2010). The results show the impact of declining prevalence on PNG parasite populations and identify the critical parameters for monitoring these changes using microsatellite markers.