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Defining the Geographical Range of the
Plasmodium
knowlesi
Reservoir
Catherine L. Moyes
1
*, Andrew J. Henry
1
, Nick Golding
1
, Zhi Huang
1
, Balbir Singh
2
, J. Kevin Baird
3,4
,
Paul N. Newton
4,5
, Michael Huffman
6
, Kirsten A. Duda
1
, Chris J. Drakeley
7
, Iqbal R. F. Elyazar
3
,
Nicholas M. Anstey
8
, Qijun Chen
9,10
, Zinta Zommers
11
, Samir Bhatt
1
, Peter W. Gething
1
, Simon I. Hay
1,12
1Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom, 2Malaria Research Centre, Universiti Malaysia Sarawak,
Kuching, Sarawak, Malaysia, 3Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia, 4Centre for Tropical Medicine, University of Oxford, Oxford, United Kingdom,
5Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR, 6Primate Research Institute, Kyoto
University, Inuyama, Aichi, Japan, 7Department of Immunology and Infection, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical
Medicine, London, United Kingdom, 8Global and Tropical Health Division, Menzies School of Health Research, Darwin, Northern Territory, Australia, 9Institute of
Pathogen Biology, Chinese Academy of Medical Sciences, Beijing, China, 10 Key Laboratory of Zoonosis, Jilin University, Changchun, China, 11 Division of Early Warning
and Assessment, United Nations Environment Programme, Nairobi, Kenya, 12 Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United
States of America
Abstract
Background:
The simian malaria parasite, Plasmodium knowlesi, can cause severe and fatal disease in humans yet it is rarely
included in routine public health reporting systems for malaria and its geographical range is largely unknown. Because
malaria caused by P. knowlesi is a truly neglected tropical disease, there are substantial obstacles to defining the
geographical extent and risk of this disease. Information is required on the occurrence of human cases in different locations,
on which non-human primates host this parasite and on which vectors are able to transmit it to humans. We undertook a
systematic review and ranked the existing evidence, at a subnational spatial scale, to investigate the potential geographical
range of the parasite reservoir capable of infecting humans.
Methodology/Principal Findings:
After reviewing the published literature we identified potential host and vector species
and ranked these based on how informative they are for the presence of an infectious parasite reservoir, based on current
evidence. We collated spatial data on parasite occurrence and the ranges of the identified host and vector species. The
ranked spatial data allowed us to assign an evidence score to 475 subnational areas in 19 countries and we present the
results on a map of the Southeast and South Asia region.
Conclusions/Significance:
We have ranked subnational areas within the potential disease range according to evidence for
presence of a disease risk to humans, providing geographical evidence to support decisions on prevention, management
and prophylaxis. This work also highlights the unknown risk status of large parts of the region. Within this unknown
category, our map identifies which areas have most evidence for the potential to support an infectious reservoir and are
therefore a priority for further investigation. Furthermore we identify geographical areas where further investigation of
putative host and vector species would be highly informative for the region-wide assessment.
Citation: Moyes CL, Henry AJ, Golding N, Huang Z, Singh B, et al. (2014) Defining the Geographical Range of the Plasmodium knowlesi Reservoir. PLoS Negl Trop
Dis 8(3): e2780. doi:10.1371/journal.pntd.0002780
Editor: Ananias A. Escalante, Arizona State University, United States of America
Received October 31, 2013; Accepted February 23, 2014; Published March 27, 2014
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for
any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: CLM and AJH are supported by the Wellcome Trust [091835]. NG is funded by a Bill & Melinda Gates Foundation grant [OPP1053338]. ZH is funded by
the Vector-Borne Disease Network. PNN is funded by the Wellcome Trust of Great Britain. MH is funded by the Asia Africa Science Platform Program of the Japan
Society for the Promotion of Science and Grants-In-Aid for Overseas Research, Japanese Ministry of Education Science awarded to Shusuke Nakazawa. CJD is
funded by a ESEI/UKRC programme grant on Plasmodium knowlesi [G1100796]. IRFE is supported by a Wellcome Trust Research Training Fellowship [B9RZGS0].
NMA is supported by a National Health and Medical Research Council Practitioner Fellowship. PWG is a Medical Research Council Career Development Fellow
[K00669X] and receives support from the Bill and Melinda Gates Foundation [OPP1068048] that also supports SB. SIH is funded by a Senior Research Fellowship
from the Wellcome Trust that also supports KAD [095066]. SIH also acknowledges support from the RAPIDD program of the Science & Technology Directorate,
Department of Homeland Security, and the Fogarty International Center, National Institutes of Health (http://www.fic.nih.gov). The funders had no role in study
design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: catherine.moyes@zoo.ox.ac.uk
Introduction
The Plasmodium knowlesi parasite, found in wild monkey
populations, is a serious public health concern yet almost nothing
is known about its geographical extent. It is known to cause severe
and fatal disease in humans [1–4] and is the most common cause
of clinical malaria in high transmission regions of Malaysia [5,6]
where it is three times more likely to cause severe malaria than P.
falciparum [4]. However, costly P. knowlesi-specific molecular
diagnostic techniques are only used to confirm diagnosis by
microscopy in one area, Malaysian Borneo, whereas human cases
have been reported from Brunei [7,8], Cambodia [9], Indonesia
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[10,11], Myanmar [12–14], the Andaman and Nicobar Islands of
India [15], the Philippines [16,17], Singapore [18–20], Thailand
[12,21–24] and Viet Nam [25,26] as well as most parts of
Malaysia [2–4,6,27–42]. The geographical limits of this disease
and the spatial variation in disease risk within these limits are
simply unknown.
Malaria caused by P. knowlesi is a truly neglected tropical disease
and there are substantial obstacles to defining the geographical
extent and risk of this disease. The symptoms of the disease in
humans overlap with those caused by other malaria parasites
[43]and other diseases such as dengue [19]. Microscopy fails to
distinguish P. knowlesi from P. malariae (a more benign infection)
and P. falciparum (the leading cause of severe malaria globally) and
in routine practice P. knowlesi is also misdiagnosed as P. vivax
[44,45]. Currently, Rapid Diagnostic Tests are not only insuffi-
ciently sensitive for P. knowlesi [46] but can misidentify this species
as P. falciparum or P. vivax (summarised in [43]), and one set of
primers used in molecular assays can mistake some P. vivax isolates
for P. knowlesi [47]. The use of routine microscopy has led to large
numbers of P. knowlesi cases being missed and the parasite is only
correctly diagnosed when costly P. knowlesi-specific molecular
techniques are used. Despite high rates of infection in parts of
Malaysia and strong evidence from laboratory experiments that
human-to-human transmission by mosquitoes is possible [48,49],
this transmission route is very difficult to demonstrate in nature
and to-date no naturally occurring human cases have been
definitively linked to human-to-human transmission [43], but
equally no barriers to natural human-to-human transmission have
been demonstrated.
In the absence of complete geographical data on this disease in
humans, the presence of alternative hosts is a useful indicator of
the potential presence of a disease reservoir. A competent
anopheline vector species is also required for transmission from
monkeys to humans (or from humans to humans). These two
factors provide an opportunity to map the potential reservoir of
the parasite in the absence of human case data. Defining areas of
risk, however, is further complicated by the fact that much of the
potential parasite range is spread over a large archipelago of many
thousands of islands separated by substantial distances; a
biogeographical factor often neglected in global disease mapping
exercises and of particular relevance to a zoonotic vector-borne
disease with a reservoir in wild mammal populations.
Previous studies have defined a range for neglected diseases
such as dengue by reviewing the consensus of evidence for the
presence/absence of the disease at each location [50]. These
studies combined multiple reports of disease presence/absence and
weighted them for diagnostic quality and reporting provenance. In
the case of P. knowlesi malaria, however, there is insufficient direct
evidence of disease presence/absence to replicate this approach. In
this study, instead of assessing the consensus of evidence for disease
presence/absence, evidence on locations of host and vector
species, as well as human case data, were combined to obtain
ranked scores for the capacity to support an infectious reservoir.
We first reviewed the evidence on non-human primate hosts and
transmission by different anopheline vector species and then
gathered data on the ranges of these two groups, as well as the
locations of known human cases of the disease. This information
was used to assess the potential of each province or island to
support an infectious reservoir. The final output is a comprehen-
sive summary of the current state of evidence for a P. knowlesi
reservoir. Importantly, it is not a map of the likelihood of a
reservoir occurring within an area but it does highlight areas
where evidence is lacking. The results of this study allow us to
propose priorities for the new data that are urgently needed in
order to understand the spatial variation in risk to humans from
this disease.
Methods
Defining the area of study
Maps of human disease often use administrative divisions to
subdivide countries. This is the structure in which much national
health data are provided and is a useful format to feed results back
to public health agencies. For zoonotic diseases, however, the
distributions of wild host species will not necessarily map closely to
administrative divisions. In this instance, the majority of cases
reported to-date are located within a huge archipelago where
administrative divisions can encompass multiple islands separated
by large distances. For this study we took a mixed approach using
administrative divisions to subdivide the mainland and the largest
islands in the archipelago (Papua, Borneo, Sumatra, Java and
Sulawesi). The largest administrative division in the area of study,
Xizang Zizhiqu (the Tibet Autonomous Region) in China, was
further divided into level two divisions. Additionally, islands
greater than 25 km from the mainland and greater than 200 km
2
in area were defined as separate geographical units. Within the
archipelago, islands within 10 km of each other were grouped
together and islands less than 100 km
2
and more than 10 km away
from any other island were disregarded. Following these approx-
imate guidelines we were able to divide this region of 19 countries
spread over approximately 25,000 islands into 475 geographical
units.
Reviewing the evidence for the pre-requisites required to
support a P. knowlesi reservoir
We conducted a literature survey in Web of Knowledge using
the terms ‘knowlesi’, ‘zoono* and malaria’, ‘monkey and malaria’
to collate journal articles on the parasite and then excluded studies
conducted solely in the laboratory (e.g. immunity studies using a
rhesus-knowlesi model). The bibliography of each article was then
searched for further published sources of information and authors
working in locations of particular interest were contacted. The
search was completed on 30 September 2013. Molecular
techniques that can distinguish the P. knowlesi parasite (alone or
in combination with microscopy) have only been available for the
last decade so this dictated the period reviewed (2004 to 2013). All
Author Summary
Plasmodium knowlesi is a malaria parasite found in
monkeys which can infect humans via mosquito bites.
People infected with the P. knowlesi parasite can suffer
severe disease and death yet this disease has often been
misdiagnosed as a different malaria type and its geo-
graphical distribution is largely unknown. The lack of data
on human infections in much of Southeast Asia means a
simple map of reported cases would likely misrepresent
the extent of the disease. Instead we evaluated and ranked
a range of evidence types according to how informative
they are about the presence of an infection risk to humans
and we mapped this ranked information. This highlighted
those geographical areas where new data on the monkey
and mosquito species involved in the infection of humans
would add most to our knowledge of the full range of
factors involved in disease risk. The resulting map
highlights known locations of the parasite, and areas
where presence of the disease in humans is unknown but
possible.
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data on wild animals tested for P. knowlesi infection were extracted
and used to determine which alternative host and vector species
would contribute to the next stage of the work.
Ranking the evidence for presence of a P. knowlesi
reservoir infectious to humans, by subnational area
Each subnational area was assigned a score based on three classes
of evidence: the presence of the parasite; the presence of a monkey
host species, and; the presence of a malaria vector species known to
bite humans (Figure 1). Each area was scored independently and
was unaffected by the scores of neighbouring areas to reflect, in part,
the patchy nature of the disease and of the evidence.
The scores assigned provide a simple ranking. In summary,
confirmation of a human infection ranked highest with +9
overriding all other evidence, then confirmation of sporozoites in
a human-biting vector scored +8. Confirmation of a monkey
infection was combined with the score for presence of a human
malaria vector (see below) to give a maximum score of +7. In the
absence of the parasite itself, presence of both a known host species
and a known vector species scored +6. Combinations of known/
putative host species presence and known/putative vector species
presence (see below) scored from +2to+5. Combinations of host
species absence, vectors species absence and absence of any
malaria in humans (see below) scored values ranging from 21to
29. In locations where both presence and absence indicators were
found, the respective scores were added together.
Scoring the evidence for P. knowlesi presence and other
human malaria parasites
All occurrences of the parasite, identified using either 1) P.
knowlesi-specific molecular identification methods or 2) a combi-
nation of microscopy and molecular techniques that distinguish P.
knowlesi from P. falciparum and P. malariae, were extracted from the
library of published literature described above. The location of
occurrence was defined as the location of infection, not the
location of symptom onset or diagnosis, and studies that could not
identify the location of infection (to state/island level) were
excluded. For each occurrence, the date of study, diagnostic
technique(s) and subnational location of infection were extracted.
Only the most recent infection from each area/island was
retained. In two studies we could not distinguish between adjacent
administrative divisions so these areas were combined (at the
Myanmar/China border and at the Myanmar/Thailand border).
Two reports of human cases from Brunei did not meet the
inclusion criteria because one used microscopy only for diagnosis
[8] and the other did not publish their diagnostic methods [7].
There were no survey results that provided clear evidence for
absence of the parasite in an area. In countries that routinely
Figure 1. This schematic outlines the system used to assign an evidence score to each area. Further details are provided in the text.
Pk =P. knowlesi.
doi:10.1371/journal.pntd.0002780.g001
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report cases of the four human malarias, occurrence of these other
species may mask P. knowlesi cases and, conversely, divisions within
these countries that report no malaria cases are less likely to have
undetected P. knowlesi cases. Areas within malaria endemic
countries reporting no malaria cases were defined using the
2012 World Malaria Report [51] and assigned a score of 23. For
areas without data in the 2012 World Malaria Report, we used the
2010 limits of P. falciparum and P. vivax defined by the Malaria Atlas
Project to classify each area [52,53].
Scoring the evidence for alternative host (monkey)
presence
Based on the data collected from published studies (see Results),
we made the decision to use the ranges of two monkey species.
Macaca fascicularis (the long-tailed or crab-eating macaque, also
known as the cynomolgus or kra monkey) and M. nemestrina (the
pig-tailed or Southern pig-tailed macaque). Two other species
have been identified as hosts, Trachypithecus obscuras and Presbytis
melalophus, however the ranges of these species fall entirely within
the range of M. fascicularis, therefore, these areas already receive
the maximum score for presence of a known non-human host
species.The ranges for M. fascicularis and M. nemestrina were initially
defined using the International Union for Conservation of Nature
(IUCN) ranges [54] and a score of +3 assigned to all subnational
areas that overlapped with one or both of these ranges. The IUCN
ranges, however, estimate the natural range of each species and do
not always include introduced populations, and new data may
have been collected since the ranges were last revised. For these
reasons we also included evidence for presence of each species
outside the IUCN ranges from 1985 onwards and gave a score of
+3 to records of a host species collected since 2000 and +2 for
records collected between 1985 and 1999. A score of +1 was
assigned to areas where the published evidence indicated
introduced populations have hybridised out with endemic species
in the area. The published literature does not cover all islands in
the Malay Archipelago so we also contacted conservation and
wildlife organisations in Indonesia, Malaysia and the Philippines to
request information on which islands support populations of these
species and assigned a score of +3 to any new areas identified by
these organisations. After published studies reported finding P.
knowlesi infections in M. nemestrina monkeys, this monkey species
was divided by taxonomists into M. nemestrina and M. leonina (the
Northern pig-tailed macaque). We made the decision to include
both species because, although it is likely that the monkeys tested
were M. nemestrina (as currently classified), human cases have been
found outside the ranges of M. nemestrina and M. fascicularis but
within the range of M. leonina. A lower score of +2 was assigned to
areas within the M. leonina range.
The IUCN ranges were combined for all three macaque species
and a score of 21 was assigned to areas outside the combined host
species range (excluding locations with introduced populations)
and 22 for those areas more than 100 km outside this range. The
maximum possible negative score was not assigned because we do
not have a definitive list of primate species that can host a reservoir
of P. knowlesi parasites in the wild, and laboratory studies have
shown that other species can be infected by this parasite [55].
Scoring the evidence for anopheline vector presence
Based on evidence from the published literature on which
Anopheles species are capable of transmitting P. knowlesi (see Results)
and evidence for which vectors transmit human malaria [56], we
assigned the highest vector score of +3 to the Leucosphyrus
Complex and the Dirus Complex. This score was assigned to areas
where a human malaria vector belonging to either of these two
Complexes was recorded as present. Specifically we used
published ranges for the Dirus Complex, Anopheles leucosphyrus
and An. latens combined, and An. balabacensis. The species were
grouped in this way because studies publishing vector species
occurrence frequently do not distinguish individual species within
these groupings. In the absence of these species, the presence of
other sylvatic vector species (forest/margins dwelling, and
therefore more likely to encounter macaques) known to transmit
malaria to humans but of unknown P. knowlesi vector status was
assigned a lower score of +2. The species in this category were the
Fluviatilis Complex, the Minimus Complex, An. koliensis,An.
aconitus,An. annularis, the Culicifacies Complex and An. flavirostris.
Finally, where no vector species from either of the above two
classes were present, presence of any of the other human malaria
vectors was assigned a lower score of +1 to reflect the fact that
these species are known to have the capacity to transmit malaria
parasites to humans [56] and have not been ruled out as vectors of
P. knowlesi. To assess the presence of all three vector classes, we
used the predicted distributions generated by the Malaria Atlas
Project [56] and defined all points with a probability of occurrence
of .0.5 as presence locations. Presence of any one of the species
from a vector class within an administrative division or island was
considered sufficient to record that vector class as present.
A score of 24 was assigned to areas outside the combined range
of the vector species and 26 to areas 100 km outside this range.
This score (smaller than the maximum negative score but greater
than the negative score assigned to absence of known monkey host
species) reflected the fact that there is a lack of evidence for the
definitive list of vectors transmitting P. knowlesi but much stronger
evidence for the definitive list of vectors that transmit malaria to
humans.
Calculating the overall score
The scores were combined as shown in Figure 1 and the overall
scores, providing a relative ranking of the cumulative evidence for
each subnational area, were displayed on a map of the region. A
second simplified map was then created, to aid visualisation of the
results, by grouping the scores into four classes: scores of +7to+9
were classed as ‘confirmed infectious reservoir’; scores of +6 were
classed as ‘confirmed reservoir prerequisites’; scores of +1to+5
were classed as ‘weak evidence for a reservoir’; and scores of 29to
0 were classed as ‘absence of reservoir prerequisites’.
To test the scores generated, the scores that would have been
obtained if evidence for presence of the parasite itself was excluded
were compared between areas with confirmed parasite presence
and those of unknown parasite status. A jackknife approach was
then used to assess the dependence of the final scores on each
individual factor. Each individual factor was excluded and the
scores were re-calculated. The results were compared between
areas with confirmed parasite presence and those of unknown
parasite status, and the relative ranking of all areas before and after
each factor was removed were compared. To assess the predictive
power of the scores, the area under the receiver operating
characteristic curve (AUC) was calculated for each version of the
scoring system created when single factors were removed in turn
(with parasite presence excluded) [57].
Results
The review of published studies of P. knowlesi infection in wild
monkey populations is summarised in Table 1. It is immediately
clear that only a few species and populations have been tested in a
few countries. High infection prevalences have been found in M.
fascicularis and M. nemestrina populations in Sarawak in Malaysian
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Borneo and lower prevalences in Singapore, Kuala Lumpur and
Pahang States in Malaysia, Narathiwat and Ranong Provinces in
Thailand, and North Sulawesi Province in Indonesia. Older
studies (pre-2004) have also found infected M. fascicularis monkeys
in Cebu, Philippines [58].
The review of published studies of P. knowlesi in wild mosquito
populations is summarised in Table 2. The most striking result is
that published studies have only been conducted in Khanh Hoa
Province in Vietnam and Pahang State and Kapit Division of
Sarawak State in Malaysia. Other countries have very different
vectors that are known to transmit malaria to humans but their
role in P. knowlesi transmission is unknown. In the areas studied,
there is evidence that Anopheles latens from the Leucosphyrus
Complex and members of the Dirus Complex transmit P. knowlesi.
Members of both Complexes are known to transmit human
malarias. Earlier studies (pre-2004) have implicated members of
the Hackeri Subgroup in transmission of P. knowlesi within monkey
populations in Peninsular Malaysia [59], however, these mosquito
species are not known to bite humans. Laboratory studies have
shown that a wider range of species may be able to transmit P.
knowlesi, however, these studies also confirmed that the most
effective vectors, of those tested, were members of the Leuco-
sphyrus Group [60,61].
The information from the reviews of monkey hosts and of
vectors was used to generate parasite, host and vector evidence
scores for each geographical area and these were combined with
the evidence for parasite presence to give an overall score
representing the evidence for potential presence of a parasite
reservoir that is infectious to humans (shown in Figure 2A). The
individual evidence scores assigned to each subnational area (for
evidence of human infection, parasite occurrence, known and
potential host occurrence, and known and potential vector
occurrence) are given in Table S1.
Figure 2A shows the full range of scores generated. The
variation in cumulative evidence for presence of the prerequisites
required to support an infectious reservoir can be seen, from a
complete absence of all prerequisites and thus evidence for
absence of a reservoir (29,) to a lack of evidence and high
uncertainty (0), to presence of a full set of prerequisites but
unknown parasite status (+6), to confirmation of human cases (+9).
Figure 2B shows a simplified version of the same information with
the scores grouped into four classes: areas where both the parasite
itself and a vector able to transmit it to humans have been found;
areas with known monkey hosts, known vectors of P. knowlesi and
no factors indicating absence of a reservoir (presence of the
parasite itself is unknown); areas of weak evidence for the presence
of a full set of reservoir prerequisites; and areas where there is
evidence for an absence of reservoir prerequisites. It is important
to note that Figure 2 is not a map of the likelihood of a reservoir
occurring within each area, for example, an area may receive a
zero score because evidence is lacking or it may in fact be less likely
to support an infectious reservoir.
Figure 3A provides a histogram of the full range of scores
assigned to the 475 subnational areas with scores +7to+9
Table 1. Published cases of P. knowlesi infection in non-human primates, from studies conducted since 2004.
No. individual monkeys positive for
P. knowlesi
infection/no. tested Ref.
M. fascicularis M. nemestrina* P. melalophus T. obscurus
Other species
Bangladesh
Bhutan
Brunei
Cambodia
China
India
Indonesia 1/31 [70]
Laos
Malaysia 10/143 0/1 0/1 [29]
71/82 13/26 [86]
Myanmar
Nepal
Palau
PNG
Philippines
Singapore 3/13 [18]
Sri Lanka
Thailand 0/99 [87]
1/195 4/449 1/7 0/4 [88]
Timor Leste
Vietnam
TOTAL 86/563 17/476 1/7 0/4
*Macaca nemestrina has since been divided into sibling species M. nemestrina and M. leonina.
doi:10.1371/journal.pntd.0002780.t001
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exclusively assigned to areas with confirmed parasite presence.
Figure 3B shows the range of scores assigned when evidence for
parasite presence was excluded from the scoring system. The
scores assigned to areas that are known to support the parasite
ranged from +1to+6, i.e. the parasite has been found in areas
outside the known monkey and/or vector ranges, or areas with
factors that indicate absence of a reservoir prerequisite. The area
that scored +5 was the northern part of Myanmar (Shan State
North and East) bordering China, and the evidence for parasite
presence here came from two independent studies [13,14]. The
known monkey host species (M. fascicularis and M. nemestrina) have
not been found in this area but M. leonina is present. Studies that
have investigated malaria parasites in the monkey populations in
this area have not yet found evidence of P. knowlesi infection in any
of the species present (Qijun Chen, unpublished data).
Two neighbouring areas with confirmed parasite presence
scored only +1 when the evidence for parasite presence itself was
excluded. These were two islands in the north of the Andaman
and Nicobar Islands; Smith Island and Car Nicobar. The southern
islands fall within the range of M. fascicularis but there is no
evidence of any known or putative monkey host species
populations on the northern islands, including Smith Island and
Car Nicobar [62]. The evidence for human P. knowlesi infections in
these locations (and also on Great Nicobar and Teressa, two of the
southern islands with known hosts and known vectors) comes from
a single study of human malaria cases in the Andaman and
Nicobar Islands [15]. A total of 15 cases were found on Smith
Island and 25 on Car Nicobar, which rules out a one-off imported
case. Further work is required to investigate the possibility of a P.
knowlesi reservoir existing on the northern islands of the Andaman
and Nicobar Islands, including the possibility of human-to-human
transmission and the possibility of a parasite reservoir in the
captive long-tailed macaques at Port Blair’s zoo [63].
Finally, Figure 2 shows that many areas in the region have weak
evidence for their ability to support an infectious reservoir, but
cannot be ruled out altogether. A small number of areas fall
outside the ranges of all known or putative hosts or vectors, which
provides evidence that these areas could not support a P. knowlesi
reservoir. If this study had covered a broader geographic area, the
number of these areas would be much higher.
Table 3 provides the AUC values calculated when evidence for
parasite presence was excluded, and each time the scoring system
was adjusted to remove a single factor in turn. The AUC value
obtained when parasite presence only is excluded was 0.7979,
indicating the scoring system has very good predictive power. No
set of factors modelled the known locations of the parasite perfectly
but the result was similar when different factors were removed and
was always &0.5, indicating that the accuracy of the scoring
system is always good and not heavily dependent on any single
factor. Figure S1 shows the full range of scores obtained when
individual factors were excluded. In each case, scores for the
subnational areas with confirmed parasite presence (31 subna-
tional areas; 29 with confirmed human cases and 2 confirmed in
monkey only) can be visualised compared to the scores for the 444
other areas. Figure S2 shows the relative ranking of the 475 areas
after a single factor has been removed, against the ranking using
Table 2. Published cases of P. knowlesi infection in Anopheles vectors, from studies conducted since 2004.
No. individual mosquitoes positive for
P. knowlesi
infection/no. tested Ref.
An. latens An. introlatus
Dirus
Complex
Hackeri
Subgroup
Riparis
Subgroup
Other Leucosphyrus
Group
Other
species
Bangladesh
Brunei
Cambodia
China
India
Indonesia
Laos
Malaysia 2/211 0/1 0/127 [29]
4/1073 0/4 0/9 0/8 0/1414 [89]
8/339 [90]
4/940 0/2 0/5 0/540 [91]
Myanmar
Nepal
Palau
PNG
Philippines
Singapore
Sri Lanka
Thailand
Timor Leste
Vietnam 37/5686 [26]
TOTAL 12/1412 0/4 43/6837 0/12 0/8 0/5 0/2081
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all factors. The relative ranking does not appear to be strongly
affected by the removal of any single factor, i.e. the individual
factors are highly correlated as indicated by the consistently high
AUC values shown in Table 3. Table S2 provides the full set of
scores for each area including the scores achieved after each
individual factor had been removed.
Discussion
By assessing the evidence in a systematic way based on the
current state of knowledge, we have been able to map subnational
areas where a P. knowlesi reservoir capable of infecting humans has
been confirmed and those that support known hosts and vectors.
In the absence of routine confirmation of P. knowlesi in human
cases, and of definitive lists of host and vector species, it is harder
to map areas of known disease absence. We have, however, been
able to classify the rest of the region into areas that range in the
evidence for their capacity to sustain a parasite reservoir that is
infectious to humans, based on the current state of knowledge.
Both the review of species shown to host and transmit P. knowlesi,
and the ranking of the evidence for a parasite reservoir, highlight
the urgent need for more evidence in large parts of the region of
study and provide information on the types of data that are
needed. The results of this study highlight priority geographical
areas for future study that would enable us to build a more precise
map. Areas of Indonesia (Kalimantan, Sumatra, part of Java and
parts of Sulawesi), parts of the Philippines, Cambodia, S.
Thailand, S. Myanmar and S. Vietnam support both the known
hosts and the known vectors, and are obvious targets for studies
investigating new locations of parasite infections and disease
prevalence. Locations with high disease potential could be
targetted further by identifying areas that report cases of P.
malariae malaria when using microscopy for routine species
confirmation. The blank cells in Tables 1 and 2 indicate the
regions that have not been tested for parasite presence in
alternative hosts and vectors, and the species that have not been
tested. In this case, data on absence of the parasite will be as
important as presence data and will help to refine the disease
limits.
When parasite presence was excluded from the scoring system,
the predictive power of the scores generated from the evidence on
hosts, vectors and human malarias was very good (AUC= 0.8146).
It is important, though, not to assume that the factors used in this
scoring system give the full picture. It is likely that the researchers
who designed the P. knowlesi studies conducted outside of Malaysia
used the same assumptions about host and vector species as this
study, when choosing their study locations, leading to a bias in
locations where the parasite has been found. Evidence from human
cases in returning travellers, however, may not be subject to the
same biases for presence of presumed host and vector species. All of
the published cases of P. knowlesi infection in returning travellers,
diagnosed outside the region, involve patients that had spent time in
one or more subnational areas where both the known monkey hosts
and the known vectors are present [7,10,17,22,30,31,34,35,37,64–
66] providing corroborating evidence for the assumptions made in
this study. Absence of a parasite is harder to prove and negative
results are harder to publish, but there is a limited amount of
unpublished data that provides further corroboration of our
approach. Investigation of 349 human malaria cases from across
Laos (average score 4.25= weak evidence) found no P. knowlesi (M.
Mayxay, unpublished data) while surveys of macaque populations in
Nepal (average score 21 = weak evidence/absence of reservoir
prerequisites) and Bangladesh (average score 1.67 = weak evidence)
also found no evidence of P. knowlesi infection (Ananias Escalante,
unpublished data).
The sensitivity analysis presented here suggests that some of the
factors included in this study could be removed and the scores
would still perform as well, however, the areas with confirmed
parasite presence are a potentially biased sample and so it would
be unwise to remove any potential factors until we are closer to a
definitive list of vectors and alternative hosts. This would help to
refine the map presented here, enabling us to assign higher
positive or negative scores for either presence or absence, and
therefore to delineate more accurately the outer limits of the
disease reservoir. This is necessary in order to provide precise
information to public health agencies, and to provide a
contemporary baseline to monitor future changes in the disease
distribution. Longitudinal studies in Sabah, Malaysia have shown
that P. knowlesi incidence has increased at this location over the last
decade [6] but further research is required to assess whether this is
linked to factors such as changing land use, changes in human
behaviour and/or changes in the behaviour of the alternative hosts
or vectors, including the possibility that human-to-human
transmission is a factor [67].
In the past a lack of diagnostics meant that data on human cases
was lacking and high population movement further complicated
the picture. We are now in a better position to obtain human case
data and this study has highlighted the regions to target. Further
studies of the monkey species able to host this parasite would also
be particularly informative, particularly in Northern Myanmar
where M. fascicularis and M. nemestrina are absent but M. leonina,M.
assamensis and T. phayrei are present [54]. Studies of any monkey
populations on Smith Island in the Andamans would also be
informative although no monkey species are endemic to this island
or nearby Car Nicobar [54] and there are no confirmed reports of
domestic or introduced primate species on these islands. Port Blair
Zoo on Smith Island has long-tailed macaques in captivity [63] but
there is no evidence for presence of captive monkeys on Car
Nicobar. The report of human cases of P. knowlesi malaria on
Smith Island and Car Nicobar [15], and the primate status of
these islands, certainly merits further investigation. Both the
monkey and vector species involved in P. knowlesi transmission are
a complex and dynamic mix of subspecies and sibling species
[56,68]. No studies to-date have considered the ability of the full
range of macaque species to host malaria parasites nor have the
many hybrids occurring in areas where these species are co-
endemic [69] been investigated for their parasite status.
As well as their susceptibility to P. knowlesi, the social
organisation of these primates differs, in terms of ranging patterns,
relationships to humans and time spent on the ground versus the
canopy. These factors may have an important influence on their
relevance as a reservoir for transmission of P. knowlesi to humans.
These factors also differ between populations; for example, in
areas with extensive primate hunting, primate reservoir popula-
tions may be pushed far from humans reducing the probability
that humans will intersect with primate-vector cycles.
This work also highlights the importance of understanding the
role of introduced populations when the ultimate goal is to map a
Figure 2. Panel A is a map displaying the evidence scores assigned to each area ranging from strong evidence for presence of a
parasite reservoir infecting humans to weak or no evidence through to absence of host and vector species indicating that an
infectious reservoir would not be supported. Panel B shows the same scores grouped into four classes.
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Figure 3. Panel A shows the distribution of scores for each subnational area. Panel B shows the scores assigned when the evidence for
parasite presence was removed (i.e. the scores based solely on host presence/absence, vector presence/absence, other human malaria presence and
presence of M. mulatta). Those areas with confirmed parasite presence are shown in black.
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disease reservoir. Plasmodium knowlesi has been found on Sulawesi
[70] where none of the host species are endemic but where M.
fascicularis and M. nemestrina are kept as pets and have escaped into
the wild [71–73]. Future studies of parasites in introduced
populations would increase our understanding of the likelihood
of a founder population being infected and of persistence of the
parasite within a new population following introduction. This
would inform the criteria used to decide which populations are
included in mapping studies.
When monkey host species have been introduced to areas where
other macaque species are endemic [74], hybrids have been found
outside the range of the host species and further interbreeding may
lead to genes from these host species being introgressed into the
native species population [75]. This again raises the question of the
infection status of hybrids and of non-host species populations with
introgressed genes from M. fasciularis or M. nemestrina. Hybrids are
likely to occur in the narrow contact zone between M. fascicularis
and M. mulatta in Thailand, Vietnam, Laos and Myanmar [76,77].
Hybrids found within the range of known P. knowlesi host species
will not impact the geographical limits of the disease, but if hybrids
are found beyond the range of the known hosts this could affect
the disease risk in these locations.
The disease status of hybrids between known hosts, whose
populations can sustain high P. knowlesi infection prevalences, and
rhesus monkeys, that may not be able to survive in the presence of
P. knowlesi, is particularly interesting and currently unknown. The
impact on P. knowlesi host status following introgression of genes
from one species into populations of another is also unknown; we
simply do not know whether introgression (contemporary or
ancient) of M. fascicularis genes into M. mulatta populations at the
southern end of their range [78–80] increases their ability to host
this parasite or whether introgression of genes from M. mulatta into
M. fascicularis populations north of peninsular Thailand reduces
their ability to act as a reservoir for this parasite, or whether more
complex genetic interactions occur. Which genes are important in
P. knowlesi infection and their status in any of these species or
populations is unknown. Taking a pragmatic approach for the
purpose of producing a map of disease risk for public health use,
however, the most important questions are 1) what is the
prevalence of human infection at precise locations and 2) what is
the prevalence of infection in species/hybrids of monkeys and
mosquitoes at precise locations across the region? A recent
preliminary finding reports a P. knowlesi infection in either a M.
mulatta monkey or a M. mulatta/M. fascicularis hybrid in Vietnam
close to the location of known human and vector infections [81].
Further investigation of P. knowlesi in wild M. mulatta populations,
and in populations of hybrids, is needed to provide evidence for
their role in hosting a parasite reservoir.
Large numbers of laboratory experiments have shown that P.
knowlesi readily infects and is usually fatal to M. mulatta (,70% of
individuals are killed) but the surviving animals have the ability to
pass the parasite on to mosquito vectors [82], leading to
contrasting hypotheses that either M. mulatta populations cannot
co-exist with the parasite [83] and could therefore be used as a
negative indicator for a disease reservoir, or M. mulatta could be a
natural host for the parasite [81] and therefore be used as a
positive indicator. Alternatively, populations of M. mulatta in
different locations may differ in their level of immunity to P.
knowlesi, which would mean both hypotheses could be true
depending on location. The overlap of the P. knowlesi parasite
and the rhesus monkey found in two subnational areas (N
Myanmar and NW Thailand) suggests the parasite and the rhesus
macaque may co-exist, however, within these two areas the precise
locations of the parasite and of the macaque may still differ. A
finer scale approach will help to resolve the question of whether M.
mulatta can co-exist with P. knowlesi. In addition, a second monkey
species, Presbytis (Semnopithecus)entellus, which is also known to have
a high fatality rate when infected in the laboratory [84], could be
used as an indicator of P. knowlesi absence or alternatively this
species could also provide a parasite reservoir. Inclusion of P.
entellus as a negative indicator would reduce the scores for areas of
Southern India and Sri Lanka on the edges of the area of this
study. More data on the naturally-occurring malaria infections
found in the full range of species in the region is needed and
further data to back up the finding of a P. knowlesi infection in
either a M. mulatta monkey or a M. mulatta/M. fascicularis hybrid in
Vietnam [81] would resolve the issue of whether M. mulatta
presence is a useful indicator for a potential disease reservoir.
The approach used in this paper has the limitation that presence
of a single isolated host population in one part of a state/island
increases the score assigned to the whole state/island. One
example of this is Papua, a Province of 320,000 km
2
which is not
endemic for any of the known or potential host species but which
supports a single isolated population of M. fascicularis near
Table 3. The area under the curve of the receiver operating characteristic for the overall model excluding evidence for parasite
presence and when individual factors were excluded in turn.
Model (scoring system) Area under the curve (AUC)
P. knowlesi presence excluded 0.7979
P. knowlesi presence and Leucosphyrus vectors excluded 0.7319
P. knowlesi presence and other sylvatic vectors excluded 0.8037
P. knowlesi presence and other human vectors excluded 0.7990
P. knowlesi presence and vector absence excluded 0.7978
P. knowlesi presence and other human malarias excluded 0.7875
P. knowlesi presence and the natural range of M. fasciularis excluded 0.8624
P. knowlesi presence and) the natural range of M. nemestrina excluded 0.7990
P. knowlesi presence and introduced Mf/Mn populations excluded 0.7808
P. knowlesi presence and M. leonina excluded 0.7970
P. knowlesi presence and host absence excluded 0.8055
Mf =M. fascicularis and Mn =M. nemestrina.
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Jayapura [85]. Surveys of the malaria parasites found in isolated
introduced populations would provide an evidence base for the
score assigned to these populations. Furthermore surveys which
show that an isolated population is P. knowlesi-free can be used to
exclude the population from the scoring system. A surveyed
population that is found to be infected will still affect the score for
the whole state/island, as will an isolated human case or infected
vectors at a single discrete location, and a finer resolution mapping
approach is needed to address this limitation of the current map.
The map presented here has divided the region into 475 areas
and provides good subnational resolution, but it is not a fine
resolution map and cannot distinguish the large variation that may
exist within a province or island. Specifically, there will be areas
within most provinces/islands that are less likely to support a
reservoir. Point-located data for the parasite, hosts and vectors is
available, which opens up the possibility of using ecological niche
modelling techniques to produce a finer resolution map. Niche
models will identify areas suitable for disease transmission that fall
outside the actual disease range, unless constrained by information
on the geographical extent of the disease. The study published
here has used an evidence-based approach to examine the putative
range of the disease reservoir and can be used to delineate outputs
from studies that use a niche modelling approach to map this
disease on a fine scale. Furthermore, the methods developed in this
study are broadly applicable and could usefully be extended to
other severely neglected vector-borne and/or zoonotic diseases
such as scrub typhus or chikungunya.
The goal of the map presented here is to provide a
comprehensive summary of the current state of evidence for a P.
knowlesi reservoir. It is not a map of the likelihood of a reservoir
occurring within each area and an area may receive a zero score
because the evidence available is lacking or it may in fact be less
likely to support an infectious reservoir. This issue is particularly
apparent within the Malay Archipelago. Smaller islands are less
likely to have evidence for parasite and/or host and/or vector
presence, but they may also differ in their underlying ability to
support a parasite reservoir. The map shows where evidence is
strong and is inherently biased to areas where studies have been
conducted. When considering methods to model the probability of
occurrence of a reservoir, on a fine-scale, it will be essential to
address the issue of sample bias. In order to produce such fine
scale maps, more data is needed and the current study has
highlighted the types of data and the geographical areas of study
that would be most informative, based on our current state of
knowledge.
Supporting Information
Figure S1 A figure showing histograms of the scores generated
each time the scoring system was adjusted. Subnational areas with
confirmed cases of knowlesi malaria in either humans or macaques
are marked in black and all other areas are light grey. Panel A
shows the scores when evidence of parasite presence is excluded.
Panels B–L show the scores generated when a second individual
evidence class is excluded: B) Leucosphyrus vectors excluded; C)
other sylvatic vectors excluded; D) other human vectors excluded;
E) combined vector range excluded; F) other human malarias
excluded; G) the natural range of M. fasciularis excluded; H) the
natural range of M. nemestrina excluded; I) introduced M. fascicularis
and M. nemestrina populations excluded; J) M. leonina excluded; K)
combined monkey range excluded.
(TIF)
Figure S2 A figure showing ranked scores generated when
individual factors were excluded. Each graph shows the ranked
scores when evidence of parasite presence is excluded (the x axis)
against the ranked scores when the score is adjusted as follows: A)
the mean score obtained across all exclusions (B–L); B) Leucosphyrus
vectors excluded; C) other sylvatic vectors excluded; D) other
human vectors excluded; E) combined vector range excluded; F)
other human malarias excluded; G) the natural range of M.
fasciularis excluded; H) the natural range of M. nemestrina excluded;
I) introduced M. fascicularis and M. nemestrina populations excluded;
J) M. leonina excluded; K) combined monkey range excluded.
(TIF)
Table S1 An Excel file containing the full set of individual scores
for each evidence class and the overall evidence score as displayed
in Figure 2A of the manuscript.
(XLSX)
Table S2 An Excel file containing the scores assigned to each
subnational area when parasite evidence was excluded and the
scores generated when each individual evidence class was
removed.
(XLSX)
Acknowledgments
The authors would like to acknowledge the important contributions made
by a number of researchers and agencies who contributed unpublished
data and helpful advice. Mayfong Mayxay provided information on the
absence of P. knowlesi in malaria patients in Laos. K. Sivakumar, Paul Holt,
Pratap Singh, and Aparna Singh all provided information about the
distribution of macaques in the Andaman and Nicobar Islands. The
Wildlife Resources Division of the Philippines Department of Environment
and Natural Resources provided information on macaque distributions by
island.
Author Contributions
Conceived and designed the experiments: CLM SIH NG. Performed the
experiments: CLM AJH ZH NG. Analyzed the data: CLM NG.
Contributed reagents/materials/analysis tools: BS JKB PNN KAD MH
CJD NMA IRFE QC ZZ SB PWG. Wrote the paper: CLM NG ZH BS
JKB PNN MH CJD NMA QC PWG SIH.
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