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.