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Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania

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Understanding rodent-ectoparasite interactions and the factors driving them is important in understanding the epidemiology of diseases involving an arthropod vector. Fleas are the primary vector for Yersinia pestis, the bacteria that causes plague and monitoring of flea population is essential for planning the potential mitigation measures to prevent the disease outbreak. In this study, we investigated flea abundance, community structure and the potential factors driving flea infestation in areas with frequent (persistent) and non-frequent plague (non-persistent) outbreaks. We collected fleas from captured rodents in two villages with both forest and farm habitats. We found 352 fleas belonging to 5 species with Dinopsyllus lypusus the most abundant overall (57.10%) and Ctenophthalmus spp. the lowest (1.70%). There were no significant differences of flea abundance between study localities, habitats and seasons (p > 0.05) but, flea infestation was significantly positively associated with the persistent locality and with the short rain season (p < 0.05). Further, flea abundance increased significantly with rodent body weight (p < 0.05). Furthermore, we found fleas broadly structured into two communities varying between the dry, long rain and short rain seasons. These findings have important implications for public health, as they may be used to assess and control the risks of plague transmission and other flea borne diseases in the foci.
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International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
Available online 4 March 2024
2213-2244/© 2024 The Authors. Published by Elsevier Ltd on behalf of Australian Society for Parasitology. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Flea infestation of rodent and their community structure in frequent and
non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Stella T. Kessy
a
,
b
,
d
,
*
, RhodesH. Makundi
b
,
c
, Apia W. Massawe
b
,
c
, Alfan A. Rija
a
a
Department of Wildlife Management, Sokoine University of Agriculture, P.O. Box 3073, CHUO KIKUU, Morogoro, Tanzania
b
The African Centre of Excellence for Innovative Rodent Pest Management and Biosensor Technology Development (ACE IRPM&BTD), Tanzania
c
Institute of Pest Management, Sokoine University of Agriculture, P. O. Box 3110, Morogoro, Tanzania
d
School of Life Science and Bio-Engineering (LiSBE), Nelson Mandela African Institution of Science and Technology, P. O. Box 447, Arusha, Tanzania
ARTICLE INFO
Keywords:
Plague
Flea abundance
Flea community
Flea-rodent interactions
ABSTRACT
Understanding rodent-ectoparasite interactions and the factors driving them is important in understanding the
epidemiology of diseases involving an arthropod vector. Fleas are the primary vector for Yersinia pestis, the
bacteria that causes plague and monitoring of ea population is essential for planning the potential mitigation
measures to prevent the disease outbreak. In this study, we investigated ea abundance, community structure
and the potential factors driving ea infestation in areas with frequent (persistent) and non-frequent plague (non-
persistent) outbreaks. We collected eas from captured rodents in two villages with both forest and farm hab-
itats. We found 352 eas belonging to 5 species with Dinopsyllus lypusus the most abundant overall (57.10%) and
Ctenophthalmus spp. the lowest (1.70%). There were no signicant differences of ea abundance between study
localities, habitats and seasons (p >0.05) but, ea infestation was signicantly positively associated with the
persistent locality and with the short rain season (p <0.05). Further, ea abundance increased signicantly with
rodent body weight (p <0.05). Furthermore, we found eas broadly structured into two communities varying
between the dry, long rain and short rain seasons. These ndings have important implications for public health,
as they may be used to assess and control the risks of plague transmission and other ea borne diseases in the
foci.
1. Introduction
Fleas are bloodsucking insects with signicant implications for
human and animal health worldwide (Bitam et al., 2010). Fleas infest a
wide range of hosts including wild and domestic animals, birds and
human (Durden and Hinkle, 2019; Zając et al., 2020; Zurita et al., 2019).
Infestation is inuenced by environmental and human behavior modi-
cations. For instance, when farmers share their dwellings with live-
stock or have corrals located in close proximity to their homes, it exposes
domestic animals and humans to infestation, leading to the transmission
of ea-borne diseases. Further, activities such as urbanization, defores-
tation, and encroachments into natural habitats, increase interactions
between human and ea-infested environments that may also increase
the risk of exposure to ea-borne pathogens (Gage et al., 2008; Bitam
et al., 2010). Fleas are well known vectors of several illness including
murine typhus caused by Rickettsia typhi, ea-borne spotted fever
caused by Rickettsia felis, cat scratch disease caused by Bartonella hen-
selae, and bubonic plague caused by Yersinia pestis (Krasnov, 2008;
Durden and Hinkle 2019; Sherman 2007). Furthermore, some eas such
as the human eas, act as vector for tape worms (Kandi et al., 2019;
Ramana et al., 2011) and pose signicant public health concerns. In
regions with sporadic ea-transmitted disease outbreaks, such as plague,
the absence of up-to-date information on ea dynamics and host infes-
tation intensies these concerns. Access to ssuch data could inform the
development of strategies to counter potential outbreaks through, for
example, targeting on reducing the population of eas and rodents.
Several factors are known to inuence ea richness and abundance
including; host diversity (Krasnov et al., 2002; Young et al., 2015), host
body condition (Bitam et al., 2010; Krasnov, 2008), host density
(Krasnov et al., 2002; Stanko et al., 2002) and climatic conditions
(Krasnov et al., 2004, 2005). However, it is not clear how such factors
are directly linked to plague persistence especially in regions with
* Corresponding author. Department of Wildlife Management, Sokoine University of Agriculture, P.O. Box 3073, CHUO KIKUU, Morogoro, Tanzania.
E-mail addresses: kessystella78@gmail.com (S.T. Kessy), rmakundi@yahoo.com (RhodesH. Makundi), apiamas@yahoo.com (A.W. Massawe), al.rija10@gmail.
com (A.A. Rija).
Contents lists available at ScienceDirect
International Journal for Parasitology: Parasites and Wildlife
journal homepage: www.elsevier.com/locate/ijppaw
https://doi.org/10.1016/j.ijppaw.2024.100921
Received 5 December 2023; Received in revised form 1 March 2024; Accepted 2 March 2024
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
2
history of disease outbreaks. Thus, understanding ea density, infesta-
tion and community structure in the plague foci may allow us to easily
predict transmission risks of ea borne diseases among co-existing
sympatric hosts. Plague is a zoonotic disease that is largely spread by
eas from rodents to humans (Gage and Kosoy, 2005). The disease
continues to be a public health concern, with over 90% of all reported
human cases worldwide originating from Sub-Saharan Africa and the
Madagascar region (Bertherat and Bertherat, 2019; Vall`
es et al., 2020).
In Tanzania, plague has been reported in several districts including
Lushoto, Karatu and Mbulu and remains a signicant potential health
risk in case of outbreak. Studying host-parasite interactions therefore
may help us to understand the risk of both persistence and outbreak of
plague. The transmission of the bacteria causing plague (Yersinia pestis),
is inuenced by various factors, including ea density in the environ-
ment (Krasnov et al., 2006a; Pham et al., 2009; Tripp et al., 2009).
Plague tends to persist in a particular locale or region when multiple
eas capable of transmitting Y. pestis infest hosts susceptible to plague
infection (Eisen and Gage, 2009), thus making the disease more or less
predictable based on known pre-disposing causes. Additionally, re-
searchers have developed statistical models and used ecological data to
predict the occurrence and distribution of plague in various regions. For
instance, Eisen et al., (2007) used a GIS-based model to predict the
habitat suitability for Yersinia pestis, in New Mexico, nding that 30.8%
of the state as suitable plague habitat, Similarly, Neerinckx et al., 2008
used ecological niche modelling (ENM) to predict the potential distri-
bution of plague occurrences across sub-Saharan Africa based on envi-
ronmental variables and occurrence data. They identied elevation,
potential evapotranspiration, mean diurnal temperature range, annual
rainfall, and Normalized Difference Vegetation Index contributing to the
plague occurrences in Sub-Saharan Africa. Furthermore, Poje et al.,
2020 studying ea populations in black-tailed dog burrow in North
America, found that the likelihood of prairie dog burrow being infested
with eas increased with high temperatures, while the prevalence of
infested burrow declined with increased winter precipitation. This, in
turn, impacted the dynamics of plague in prairie dog colonies.
Several studies have reported disease persistence and transmission
conditions in Mbulu districts, Tanzania (Makundi et al., 2008; Ziwa
et al., 2013). High ea diversity and rodent hosts richness, with a
multiple host-ea interaction in different habitats are variables that
contribute to plague persistence in this focus (Makundi et al., 2015). A
more recent study has shown plague bacteria continues to circulate
among susceptible rodents in Mbulu district (Haikukutu et al., 2022),
suggesting potential risks of plague outbreak. These studies suggest that
regular monitoring and updating data on the ea-rodent interactions
and the likely factors driving potential outbreaks and disease persistence
are important to control the disease in these rural communities. This can
be achieved through public awareness campaigns and educational pro-
jects that inform and educate residents about lifestyle practices that
encourage ea-rodent-human interaction. Additionally, community
engagement is crucial, with health ofcers visiting local communities to
identify possible risks and provide valuable guidance as well as devel-
oping strategies that target both ea vector and rodent hosts.
In this study, we aimed to provide current information on the ea
infestation of rodents, their community structure and how infestation
varied between plague persistent and non-persistent foci in Mbulu dis-
trict, northern Tanzania. Specically, we (i) assessed rodent ea abun-
dance in different habitats, seasonality, and localities contrasting in
plague outbreaks, (ii) examined which factors inuence prevalence of
ea infestation, (iii) assessed the effect of habitats, seasons, temperature,
humidity and rodent species traits (sex, sex condition, species ID,
weight) on overall ea abundance and, (iv) assessed how ea commu-
nity structures between localities in different habitats and its potential
hosts. We predicted that ea load would be greater in plague persistent
than non-persistent localities and we predicted that ea abundance and
infestation would be positively associated with seasonality and plague
persistent locality due to available hosts and suitable habitats and
environmental conditions that would provide ea population growth.
Finally, we predicted that ea species would be structured according to
similar resources such as blood meals from host animals, microclimate
conditions, and habitats use, and that some ea species should show host
preferences while others exhibit host sharing pattern between multiple
hosts, providing conducive environment for the disease enzootic
circulation.
2. Materials and methods
2.1. Study area
This study was conducted in two villages, Mongahay (0403
S, 35
26
E) and Endesh-Arri (0403
S, 3527
E) located in Mbulu District,
Manyara Region in Northern Tanzania from Jan 2019 to Dec 2019
(Fig. 1). The villages were chosen based on the plague outbreak history
and presence of plague pathogen in the rodent population (Makundi
et al., 2008; Ziwa et al., 2013; Mwalimu et al., 2022). Villages with and
without human plague cases were purposefully selected in consultation
with village leaders. Villages with a history of bubonic plague cases were
identied as plague persistent(Endeshi village), while those without a
history of bubonic plague were identied as non-persistent(Mongahay
village). Both villages engaged in crop farming and livestock keeping as
their primary economic activities.
The district where the study villages are lies between 1000 and
2400m above sea level and is characterized by bimodal rainfall pattern,
with a long rainy season between March and May, and a short rainy
season between November and January (Nyembo et al., 2021). The short
rain season is characterized by sporadic and light rainfall, which is less
predictable. During the short rain season the mean temperature was on
average 16.84 C (SE =0.13). On the other hand, the long rain season is
characterized by cloudy skies and heavy rainfall, with mean tempera-
ture of 14.79 C (SE =0.12).
2.2. Rodent trapping
Rodents were live trapped using Sherman traps (LFA 7.6 x 8.9 ×23
cm, H.B. Sherman Trap, Inc., Tallahassee, USA) baited with peanut
butter mixed with maize our. Five transect lines with 10 trapping
stations set 10 m apart were established in the natural forest (natural
forest) and farmland (mixed farming) habitats in each village (Kessy
et al., 2023). Traps were left overnight and inspected each morning for
three days. Trapping was conducted every month for 15 months be-
tween Jan 2019 to Dec 2019.
Captured animals were anaesthetized with diethyl ether for immo-
bilization (Palomino et al., 2020). Morphological measurements
(weight, head body length, tail length and ear length) and other char-
acteristics of each captured animal (sex and reproductive status) were
recorded. Sex condition were noted as indicators of reproductive status
of the host species i.e. the position of the testes, vagina and nipples.
Females were classied as virginal perforated (PSN), perforated and
lactating (PLY), virginal closed (CSN), perforated small nipple with
young ones (PSY) and perforated lactating not pregnant (PLN). Males
were classied as scrotal visible (SV) as active males and testes were
abdominal (AN) as non-active male (Makundi et al., 2007). Rodents
were identied to species level using Happold (2013) and conrmed by
sequencing the mitochondrial cytochrome b gene at the Institute of
Vertebrate Biology, Czech Republic.
2.3. Flea collection
Rodents were removed from the holding bag and carefully brushed in
a pan to remove eas. Each bag was thoroughly checked to remove
dislodged eas and the tray was examined carefully with a hand lens to
remove all ectoparasites using a moistened paint brush.
Fleas were grouped based on locality, habitat, month, and host
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
3
species and were counted and preserved in 70% ethanol for future
identication. The eas were then processed by adopting a modied
version of the method described in (Philip Samuel et al., 2021). Briey,
each group was exposed to NAOH 10%, dehydrated in various concen-
trations of ethanol (50%, 70%, 95%, absolute), cleared in clove oil,
temporarily mounted using glycerin on a microscopic slide, and exam-
ined under a light microscope using a 10x objective.
To understand how local climatic parameters inuence eas in the
area, rain data were measured and recorded using an ordinary rain
gauge installed outside Mongahay village ofce between Jan 2019 to
Dec 2019. Data were recorded every day, and monthly mean values
were calculated. We also collected atmospheric temperature, and rela-
tive humidity data using data loggers (Thermochron iButtons ®), with
two data loggers placed under trees in each locality. We considered trees
that had dense canopy so that they could give enough shades throughout
the day. The iButton data were downloaded once a month. The monthly
mean values of temperature (C), and humidity (%) were calculated.
2.4. Data analysis
To establish ea abundance, we grouped ea data collected from
each rodent host species and across the sampled sites and tested for
normality using Shapiro test (P <0.05). Flea abundance is used here to
refer to the total number of eas collected for each rodent host and
sampled sites during the sampling period regardless of the species
identity. To assess how ea abundance varied between localities, habitat
types and season, we used the Mann-Whitney-Wilcoxon test to explored
signicant differences of ea load between habitats and localities.
Similarly, the Kruskal-Wallis test was used to assess differences in ea
abundance across ea species and seasons as well as differences of each
ea species across rodent species and habitats in each locality (Npfarm
=farm in non-plague persistent locality, Npforest =forest in non-
persistent locality, Pfarm =farm in persistent locality and Pforest =
forest in persistent locality).
Further, to assess how temperature, humidity, rainfall, and rodent
species traits (sex, sex condition, rodent species, weight, head body
length) inuenced ea abundance, we built a negative binomial
generalized linear mixed model (GLMM) implemented in the ‘lme4
package. Prior to modelling, we examined the data variables for po-
tential multicollinearity among temperature, rainfall, the weight, head
and body length variables. We subsequently dropped rainfall from the
model and retained temperature as these were highly correlated (r =
0.51) and because temperature is known to inuence ea growth and
development (Cavanaugh and Marshall 1972; Kreppel et al., 2016; Ming
ming et al., 2013). The rst model included sex, sex condition, head and
body length, temperature, weight and humidity as xed factor and ro-
dent species as random factor. The relative inuence of each variable in
the model was evaluated by deleting non-signicant model term in a
backward step-wise process, assessing model variance at each step of the
modelling. The drop1 function was used to delete non-signicant term
along each modelling steps and model signicance assessed using the
Wald test (Bolker et al., 2009). The best model tting the data was
chosen using the Akaike Information Criterion (AIC).
Furthermore, the binomial generalized linear model (GLM) imple-
mented in the MASS package was used to examine the probability of ea
infestation as a function of localities, habitats, seasons and rodent spe-
cies. Flea infestation-referred as presence or absence was treated as a
dependent variable in the model. To understand the relative inuence of
each variable in the model similar procedure as performed above was
followed. Further, the relative risk ratio (RR) of each independent var-
iable was computed from exponentials of coefcients generated from the
best models. To understand how these factors from the best model were
able to predict the ea load and prevalence of ea infestation, we built
prediction models using the ‘predict function with the ggplot2
pack-
age. All modelling analyses were performed in R program, version 4.3.1.
Finally, to assesses species interaction and how ea community
structures between localities, habitats and seasons we used cluster
analysis based on a Bray-Curtis similarity matrix of grouped variables
with the program PRIMER v6. To obtain this, abundance matrix data
were rst square root transformed to down weight high abundance data,
Fig. 1. A map of Mbulu district indicating the two study localities, Endeshi-Arri (Persistent locality and Mongahay (non-persistent locality), along with the two study
habitats (Farmland and forests) in each locality.
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
4
normalizing them and creating a resemblance matrix. Further, we
visualized whether ea species clustered based on locality, habitat, and
season using a dendrogram plot.
3. Results
3.1. Abundance of eas in the study area
A total of 352 eas belonging to 5 species were collected, with
Dinopsyllus lypusus being the most abundant species, comprising 57.10%
of the total (n =201), followed by Xenopsylla brasiliensis at 29.26% (n =
103), Nosopsyllus spp. at 8.52% (n =30), Xenopsylla cheopis at 3.41% (n
=12) and Ctenophthalmus spp. at 1.70% (n =6).
A total of 420 individuals belonging to 12 species within family
Muridae were captured. Among all species, Mastomys natalensis had the
highest number of captures compared to other species in different
habitats and localities. Additionally, the short rainy season had higher
number of rodent hosts compared to other seasons. The total number of
rodent hosts for each species across habitats, localities, and seasons is
presented in Table 1.
Flea abundance by ea species across rodent hosts and habitats
revealed that, cultivated land, ea abundance was dominated by
D. lypusus, accounting for 48.26% (n =83) of the total ea population,
followed by X. brasiliensis at 36.63% (n =63), Nosopsyllus spp. at 9.30%
(n =16), and X. cheopis at 5.82% (n =10). Among the rodent species,
Mastomys natalensis had the highest ea abundance at 66.28% (n =114),
followed by Aethomys kaiseri at 24.42% (n =42). In the forest habitat,
D. lypusus was also the most abundant ea species, accounting for
65.56% (n =118) of the total ea population, followed by X. brasiliensis
at 33.89% (n =40), Nosopsyllus spp. at 11.86% (n =14), Ctenophthalmus
spp. at 3.33% (n =6), and X. cheopis at 1.69% (n =2).
The plague persistent locality had the highest ea abundance
71.88% (n =253) compared to non-persistent locality 28.13% (n =99).
On the habitat types, the forest had the highest ea abundance 51.14%
(n =180) compared to cultivated areas 48.86% (n =172). Also, ea
abundance was highest in the short rain season 59.94% (n =211) than
the long rain season and dry season (22.73%, n =80 and 17.33%, n =
61; respectively). Furthermore, there were signicant differences in ea
abundance between ea species (
χ
2
=11.69, df =4, p =0.02). There
were no signicant differences in ea abundance between localities (W
=1744, p =0.68), habitats (W =2157, p =0.83) and seasons (
χ
2
=
5.04, df =2, p =0.08) (Fig. 2ac).
The rodent species with the highest ea abundance were Mastomys
natalensis at 32.22% (n =58) and Praomys delectorum at 30.56% (n =55)
(Fig. 3). When assessing how each ea species varied between rodent
species and habitats in each locality; there was a signicant difference in
X. Brasiliensis abundance between rodent species (
χ
2
=25.55, df =11, p
=0.01). A Signicant higher abundance of X. Brasiliensis was observed
on M. natalensis compared to Mus cf. gratus (p =0.03), Grammomys cf.
macmillan (p =0.01) and Lophuromys makundii (p =0.02). However,
there were no signicant difference in X. brasilliensis abundance between
habitats of each locality (
χ
2
=1.03, df =3, p =0.79). Similarly, the
abundance of D. lypusus species varied signicantly between rodent
species (
χ
2
=26.16, df =11, p =0.01). Mastomys natalensis had
signicantly higher abundance of D. lypusus compared to Mus minutoides
(p =0.03), Mus gratus (p =0.02), Lophuromys makundii (p =0.01),
Graphiurus cf. raptor (p =0.03), and Lemniscomys striatus (p =0.01). No
signicant differences were found in D. lypusus abundance between
habitats of each locality (
χ
2
=3.19, df =3, p =0.36). Furthermore, the
abundance of X. cheopis varies signicantly between rodent species (
χ
2
=20.26, df =11, p =0.04). Mastomys natalensis had signicantly higher
abundance of X. cheopis compared to Mus minutoides (p =0.04),
Lophuromys makundii (p =0.02), Graphiurus cf. raptor (p =0.02), Lem-
niscomys striatus (p =0.02), Grammomys cf. macmillan (p =0.01) and
Arvicanthis sp. Masai Mara. No signicant differences in X. cheopis
were observed between habitats in the locality (
χ
2
=0.87, df =3, p =
0.83). Moreover, there was a signicant difference in Nosopsyllus spp
abundance between rodent species (
χ
2
=32.31, df =11, p <0.05), with
M. natalensis having higher abundance compared to all other rodent
species (p <0.05). However, there were no signicant difference in
Nosopsyllus spp abundance between habitats in the locality. Addition-
ally, the abundance of Ctenophthalmus spp did not vary signicantly
between rodent species (
χ
2
=17.75, df =11, p =0.08) and between
habitats in the localities (
χ
2
=3.83, df =3, p =0.28).
3.2. Factors inuencing ea abundance
The model results indicated rodent weight was signicantly and
positively correlated with ea abundance (mean =0.02 ±0.004SE, p <
0.05) Fig. 4a). Furthermore, male rodents had higher ea abundance
than females (mean =0.27 ±0.158SE, p =0.09; Fig. 4b).
3.3. Effect of locality, season, habitat and rodent species on probability of
ea infestation
The highest probability of ea infestation was mostly associated with
the plague persistent locality. Similarly, there was a signicant effect of
the short rain season on the probability of higher ea infestation.
(Table 2, Fig. 5).
3.4. Flea community structure in the plague foci
Cluster analysis based on the ea abundance data revealed two
distinct ea community structures based on the habitats. The dendro-
gram plot (Fig. 6) showed that ea species were clustered into two main
groups, group A comprising of four species (Nosopsylla spp., Xenopsylla
Table 1
Number of rodent species captured across localities, habitats (Pfarm =farm in plague persistent locality, Pforest =forest in plague persistent locality, NPfarm =farm in
non-plague persistent locality and NPforest =forest in non-plague forest) and seasons.
Rodent species Localities Seasons
Pfarm (n) Pforest (n) Plague locality (n) NPFarm (n) NPForest (n) Non-plague locality (n) Dry Long rain Short rain
Aethomys kaiseri 17 0 17 6 0 6 12 4 7
Arvicanthis sp. Masai Mara" 6 0 6 2 0 2 0 0 8
Grammomys cf. macmillani 4 16 20 0 3 3 7 4 12
Graphiurus cf. raptor 0 5 5 0 4 4 0 0 9
Lemniscomys striatus 0 14 14 0 1 1 1 1 13
Lemniscomys zebra 2 0 2 3 0 3 1 0 4
Lophuromys makundii 0 32 32 0 0 0 9 12 11
Mastomys natalensis 113 9 122 54 31 85 49 36 122
Mus cf. gratus 0 2 2 0 1 1 0 2 1
Mus minutoides 8 0 8 1 0 1 6 2 1
Praomys delectorum 0 81 81 0 4 4 29 13 43
Rattus ratus 1 0 1 0 0 0 0 0 1
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
5
cheopis, Dinopsyllus lypusus, and Xenopsylla brasiliensis) and group B
consisting of only one species (Ctenophathalmus spp). Group A had a
ner-scale separation of the two subgroups, with Nosopsylla spp. and
Xenopsylla cheopis clustering together and Dinopsyllus lypusus and Xeno-
psylla brasiliensis forming a separate cluster. Furthermore, ea commu-
nities were structured based on habitat, with some ea species
Fig. 2. Flea abundance in the (a) localities, (b) habitats and (c) seasons. Error bars represent the standard error. There were no statistically signicant differences that
were observed.
Fig. 3. Flea abundance for different ea species across habitat types in each locality and rodent species.
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
6
associated with both forest and cultivated land, while others were
associated with only forest habitats.
4. Discussion
This study aimed to understand the pattern of ea abundance be-
tween localities, habitat type, and season. Flea abundance was found to
be similar between localities and seasons. However, the study found that
ea infestation was mostly associated with the plague persistent locality
and the short rain season. Furthermore, ea abundance was found to
have a signicant positive correlation with rodent weight. In addition,
ea community was structured into two distinct groups.
We did not nd signicant difference in ea abundance between the
localities, despite the hypothesis that the plague persistent locality
would have higher ea abundance. This observation seems to contradict
the hypothesis that high ea abundance in persistent localities increases
the risk of bubonic plague. However, it is important to note that the
study found that the probability of ea infestation was signicantly
higher in the plague persistent locality, indicating that the risk of plague
pathogen spreading may still be elevated in this locality. One possible
explanation for the lack of signicant difference in ea abundance be-
tween the localities could be differences in the ea species assemblage
and level of infestation among different hosts. Even if the ea abundance
is similar, the composition of ea species and the levels of infestation on
individual host species could still be important determinant of disease
persistence, consistent with the available literature (Eisen et al., 2012).
Moreover, we did not nd any signicant differences of ea abundance
between seasons, but we observed that rodents were more frequently
infested with eas during the short rain season. This observation may be
attributed to the warmer and more humid conditions during the short
rain season, which create a favourable environment for ea develop-
ment and survival, leading to increased infestation in rodents. These
ndings align with previous studies which have shown that warmer and
humid condition promote ea development and survival, leading to
higher ea abundance (Krasnov et al., 2001; Kreppel et al., 2016; Sharif
1949; Mboera et al., 2011; Ngeleja et al., 2017), Importantly, such
condition has also been associated with an elevated incidence of human
plague in some of the plague foci. For example, Debien et al. (2010)
reported that precipitation resulted in higher ea abundance and an
increased incidence of plague in Lushoto, Tanzania.
Further, we found a positive association between rodent weight and
ea abundance. We also found a positive association between male ro-
dents and ea abundance, which is often attributed to their larger body
size (Moore and Wilson, 2002), but this relationship was not signicant
in our study area. Mostly, male rodents tend to have higher ea abun-
dance due to their larger body size, ample blood supply, weaker im-
munity and less grooming ability (Eads and Hoogland, 2016; Kiffner
et al., 2013). In addition, larger rodents tend to have higher activity
levels, which could increase their exposure to eas in the environment
(Krasnov et al., 2006b). However, different species can vary from these
patterns, and more studies are necessary to better understand relation-
ship between rodent weight and ea-borne diseases enabling more in-
sights into their specic host-ea relationships.
Furthermore, we found two communities of eas in the foci, sug-
gesting the ea community structures were inuenced by the seasons,
habitats types and hosts present in these habitats. These results are
consistent with studies elsewhere which have shown strong ea-habitats
(Brinkerhoff, 2008), host-habitat relationships (Krasnov et al., 2006)
and environmental factors (Chotelersak et al., 2015). In the present
study, the rst ea community included Dinopsyllus lypusus,
X. brasilliensi, X.cheopis and Nosopsyllus spp. which were found in both
Fig. 4. Plots showing predicted effect of rodent traits on ea abundance, based on nal best tting generalized linear mixed model with a negative-binomial
function. The plots (a) indicates that rodent weight increased with ea abundance. The gray shade in the plots represents the strength and direction of the corre-
lation, with the width of the shade indicating the 95% condence interval (CI) around the estimated effect. Furthermore, plot (b) indicates that male rodents are more
likely to have higher ea abundance compared to female rodents, but this association was not statistically signicant. The bars are 95% condence intervals of
the effects.
Table 2
Effect size with standard errors (±SE) and relative risk ratio (RR) of localities
and seasons on the probability of ea infestation, from the nal best tting
Generalized Linear Model (GLM) model.
Predictors Estimate (SE) RR RR 95% CI z-value p-value
(Intercept) 2.09 (0.49) 0.12 0.050.32 4.23 <0.001
Locality
Plague persistent 1.01 (0.45) 2.75 1.156.58 2.27 0.02
Season
Long rain 0.16 (0.57) 0.84 0.272.63 0.29 0.77
Short rain 0.98 (0.51) 2.69 0.987.36 1.93 0.05
Non-persistent locality and dry season were dened as reference.
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
7
farm and forest habitats. The species prefer rodents as primary hosts. For
example, X.cheopis, Dinopsyllus lypusus, and X. brasilliensis prefer R. ratus
as a primary host (Msangi, 2019), but they can also infest other rodent
species (Palazzo, 2011; Trivedi, 2003). However, a ne scale separation
observed in this group may be connected to the habitat types, seasons
and/or other factors in the foci, further studies would be needed to
conrm this hypothesis. Dinopsyllus lypusus, and X. brasilliensis, have
been reported as potential vector of plague among sylvatic rodents
(Ziwa et al., 2013) and the species were found on commensal rodent
such as Ratus rattus and M. natalesnsis, and on wild rodents such as
P. delectorum and L. makundii (Fig. 2a), indicating a ea-host-habitat
association. In addition, other studies have revealed that Xenopsylla
species is primarily an efcient vector of plague to humans (Zhang et al.,
2015; Hinnebusch et al., 2017). Moreover, M. natalensis is a social spe-
cies that nests in burrows and occasionally associates with other wild
rodent species (Coetzee 1975); given that Y.pestis is still circulating in
this species in the foci (Haikukutu et al., 2022), the diverse ea infes-
tation on M.natalensis may be contributing to plague persistence in the
foci and possibly inuencing spreading of Y.pestis between other rodent
species and/or other hosts sharing these habitats. In the second ea
community, Ctenophthalmus spp. were found to be the only species. The
species was only present in forest habitats, suggesting a strong associa-
tion with areas characterized by vegetation, such as grassy and wooded
environments. Additionally, their presence in rodent burrows and nests
reinforces their connection to habitats where these particular hosts were
commonly located. The species was found on host M. natalensis and
P. delectorum which was consistent with previous ndings conducted in
the same study area (Haule et al., 2013). The state of the forest habitat
supporting more diverse ea species compared to the farms, and pres-
ence of some of ea species infesting multiple rodent hosts that includes
Fig. 5. Plot showing the predicted effect of locality and season on the probability of ea infestation, based on the nal best-tting generalized linear model with a
binomial function. The analysis aimed to identify the factors that strongly inuence ea infestation. The strongest predictors of ea infestation were plague persistent
localities and short rain seasons. The probability of infestation on these predictors was found to be statistically signicant (p <0.05), suggesting a higher likelihood of
ea infestation in this locality and season. The bars are 95% condence interval of the effects.
Fig. 6. Dendrogram of ea species showing two main groups (AB) of ea community based on farm and forest habitats.
S.T. Kessy et al.
International Journal for Parasitology: Parasites and Wildlife 23 (2024) 100921
8
the susceptible species may encourage the potential of epizootic cycle of
disease transmissions between rodent species. Alarmingly, these ea
species have the ability to harbor other zoonotic pathogens such as
Bartonella and Richettsia typhi (Leulmi et al., 2014; Occhibove et al.,
2022) highlighting the need for more studies on ea borne pathogen
pattern and their role as pathogen vector in the foci.
5. Conclusion
Our ndings provide insight into the complex interactions between
ea communities, rodent host species and environmental factors in the
plague foci. The observed ea vector associating with sylvatic host, its
ability to harbor other zoonotic pathogens inuences the relevance of
extending our study to a broader disease transmission dynamic within
the foci. Our data about these ecosystems, provide opportunities for
potential strategies to targeted public health interventions that can
lower risks of bubonic plague and other ea borne diseases in these rural
communities.
Ethical approval
Ethical clearance was obtained from Sokoine University of Agricul-
ture Ref. no DPRTC/R/126/182/38, Manyara region Ref. no FA.262/
347/01/H/247, Mbulu district Ref. no AB.323/381/01/B/9. Animal
handling followed the guidelines of the American Society of Mammol-
ogists (ASM) for the use of wild mammals in research and education
(Sikes & Animal Care and Use Committee of the American Society of
Mammologists, 2016).
Author contributions
STK designed, conducted eld data collection, data analysis and
wrote original draft manuscript. AAR analyzed the data and reviewed
the original drafts. RHM and AM reviewed the manuscripts. AAR, RHM
& AM supervised the research. All authors read and approved the nal
version of the manuscript for submission.
Data availability
All data used in this analysis can be obtained from the corresponding
author upon request.
Funding
The study was funded by the African Centre of Excellence for Inno-
vative Rodent Pest Management and Biosensor Technology Develop-
ment (ACE IRPM&BTD) ACE IICredit number 5799TZ at Sokoine
University of Agriculture, Morogoro, Tanzania.
Declaration of competing interest
The authors declare that they have no conict of interest.
Acknowledgements
Many thanks to the community leaders and local people of Endesh
and Mongahay villages in Mbulu district for allowing us to conduct this
study. Thanks to the technical staffs for the assistance in eld trapping
and animal processing. We also extend our thanks to Professor Josef
Bryja, Institute of Vertebrate Biology, Czech Republic for rodent species
identication.
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S.T. Kessy et al.
... En cuanto a C. felis, Baak-Baak et al. (2016) reportaron una prevalencia menor, pero con una abundancia mayor a la obtenida en este estudio. El tamaño, peso y densidad corporal del huésped influyen en la riqueza y abundancia de las pulgas, por lo que en roedores los parámetros ecológicos suelen ser bajos (Bitam et al., 2010;Clark et al., 2018;Kessy et al., 2024). ...
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El municipio de Celestún forma parte de la Reservas de la Biosfera Ría Celestún (RBRC), en Yucatán, México. Debido a que la reserva natural es diversa en flora y fauna hay gran afluencia de turistas. En contraste, también son abundantes los roedores sinantrópicos de las especies Mus musculus (Linnaeus, 1758) y Rattus rattus Linnaeus, 1758. Estos roedores son reconocidos como portadores de patógenos que pueden ser potencialmente transmitidos a animales y humanos por medio de los ectoparásitos. El objetivo del trabajo fue determinar la abundancia de los roedores M. musculus y R. rattus en domicilios de Celestún y estimar algunos parámetros ecológicos de sus ectosimbiontes. La captura de roedores sinantrópicos se realizó en 25 domicilios entre julio y diciembre de 2023. Se capturaron un total de 82 roedores, 59 de la especie M. musculus y 23 R. rattus. De ambos roedores se recolectaron 551 ectosimbiontes pertenecientes a seis taxones. En R. rattus se identificaron ectoparásitos de importancia médica, correspondientes a 42 ejemplares del ácaro mesostigmado Laelaps echidninus Berlese, 1887 (Acari: Mesostigmata) y un ejemplar de pulga de la especie Ctenocephalides felis Bouché, 1835 (Siphonaptera: Pulicidae). Los ácaros mióbidos Radfordia affinis Poppe, 1896 (Acari: Sarcoptiformes), Myobia murismusculi Schrank, 1781 (Acari: Sarcoptiformes), el miocóptido Myocoptes musculinus Koch, 1844 (Acari: Trombidiformes) y ejemplares de la familia Listrophoridae se encontraron exclusivamente en M. musculus, representando los primeros registros para el estado de Yucatán, en el sureste de México.
... Indeed, in Uganda, the Xenopsylla index increased prior to the onset of the annual plague, particularly in years with human cases [29]. Similarly, the concentration of rodents in a few places can increase the risk of an outbreak, as described by Carlson et al. [30] and by Kessy et al. [31], who reported an increase in domestic flea bites in rural areas during the dry season prior to plague transmission. ...
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Plague is a zoonotic disease caused by Yersinia pestis, and it is endemic in Madagascar. The plague cycle involves wild and commensal rodents and their fleas; humans are an accidental host. Madagascar is the country where plague burden is the highest. Plague re-emerged in Mahajanga, the western coast of Madagascar, in the 1990s and infected populations in the popular and insalubrious zones. Sanitation is considered a primary barrier to infection by excluding pathogens from the environment and reservoirs. Poor housing and hygiene and proximity to rodents and fleas in everyday life are major and unchanged risk factors of plague. The aim of this study was to measure the impact of sanitation on Yersinia pestis bacteria in human and small mammal reservoirs and flea vectors. This study was conducted on 282 households within 14 neighborhoods. Two sessions of sampling were conducted in 2013 and 2016. Small mammals were trapped inside and around houses using live traps. Fleas, blood and spleen were sampled to detect Y. pestis infection and antibodies and determine the level of plague circulation before and after the installation of sanitation in order to assess the impact of sanitation improvement on inhabitant health. Two major types of housing can be described, i.e., formal and informal (traditional), scattered in all the suburbs. Among the small mammals captured, 48.5% were Suncus murinus, and 70% of houses were infested. After sanitation, only 30% of houses remained infested, and most of them were located around the market. Fleas were mostly Xenopsylla cheopis. Before and after intervention, the overall prevalence of fleas was the same (index 4.5) across the 14 suburbs. However, the number of houses with fleas drastically decreased, and the flea index increased significantly in rodent-infested houses. Rodent abundance also decreased from 17.4% to 6.1% before and after intervention, respectively. A serology study highlights that plague is still circulating in Mahajanga, suggesting that small mammals maintain enzootic plague transmission in the city.
... Fleas, mainly the rat flea (Xenopsylla cheopis), are well-known vectors of plague, a disease caused by the bacterium Yersinia pestis. While plague is less common today, it remains endemic in some regions, and climate variations can influence flea populations and the prevalence of plague outbreaks 42,43 . Fleas also transmit murine typhus, caused by Rickettsia typhi, which can be influenced by climatic factors affecting rodent populations and flea activity 44 . ...
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Climate change is increasingly recognized as a significant driver of ecological and public health changes, particularly concerning vector-borne diseases. This scoping review aims to systematically map the current research on the impact of climate change on vector ecology and the subsequent effects on disease transmission dynamics. We conducted a comprehensive literature review across multiple databases to identify critical vectors, such as mosquitoes, ticks, and fleas. We examined how climate variables like temperature, precipitation, and humidity affect their populations, behaviors, and life cycles. Additionally, we explored the shifting geographic distributions of these vectors, investigating how climate change influences their spread and the emergence of diseases such as malaria, dengue, and Lyme disease in new regions. The review highlights the complex and multifaceted interactions between climate change and vector-borne diseases, emphasizing the necessity of understanding these relationships to inform effective public health strategies. Our findings indicate considerable variability in the impacts of climate change across different regions and vector species, underscoring the need for localized studies and tailored interventions. Moreover, significant research gaps were identified, particularly in predictive modeling, long-term surveillance, and the socio-economic impacts of vector-borne diseases exacerbated by climate change. We suggest directions for future research, including the development of integrated climate health models and enhanced disease surveillance systems to better anticipate and mitigate the effects of climate change on vector-borne disease transmission. This review underscores the urgency of addressing climate change as a critical component of global health initiatives and the importance of interdisciplinary approaches in tackling this complex issue
... Such studies, if available could be useful in revealing the potential risks of parasites and diseases transmission across the houses and surroundings in rural areas. 19 Also, few studies have examined the ecology and movement of M. natalensis in areas immediately adjacent to houses, which are nonpreferred habitats. 20,21 The literature has shown that R. rattus tend to prefer residential areas, 22 but there is limited information on their movement from inside houses to areas surrounding houses and other habitats. ...
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... Fleas, mainly the rat flea (Xenopsylla cheopis), are well-known vectors of plague, a disease caused by the bacterium Yersinia pestis. While plague is less common today, it remains endemic in some regions, and climate variations can influence flea populations and the prevalence of plague outbreaks 42,43 . Fleas also transmit murine typhus, caused by Rickettsia typhi, which can be influenced by climatic factors affecting rodent populations and flea activity 44 . ...
... Fleas, mainly the rat flea (Xenopsylla cheopis), are well-known vectors of plague, a disease caused by the bacterium Yersinia pestis. While plague is less common today, it remains endemic in some regions, and climate variations can influence flea populations and the prevalence of plague outbreaks 42,43 . Fleas also transmit murine typhus, caused by Rickettsia typhi, which can be influenced by climatic factors affecting rodent populations and flea activity 44 . ...
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Climate change is increasingly recognized as a significant driver of ecological and public health changes, particularly concerning vectorborne diseases. This scoping review aims to systematically map the current research on the impact of climate change on vector ecology and the subsequent effects on disease transmission dynamics. We conducted a comprehensive literature review across multiple databases to identify critical vectors, such as mosquitoes, ticks, and fleas. We examined how climate variables like temperature, precipitation, and humidity affect their populations, behaviors, and life cycles. Additionally, we explored the shifting geographic distributions of these vectors, investigating how climate change influences their spread and the emergence of diseases such as malaria, dengue, and Lyme disease in new regions. The review highlights the complex and multifaceted interactions between climate change and vector-borne diseases, emphasizing the necessity of understanding these relationships to inform effective public health strategies. Our findings indicate considerable variability in the impacts of climate change across different regions and vector species, underscoring the need for localized studies and tailored interventions. Moreover, significant research gaps were identified, particularly in predictive modeling, long-term surveillance, and the socio-economic impacts of vector-borne diseases exacerbated by climate change. We suggest directions for future research, including the development of integrated climate-health models and enhanced disease surveillance systems, to better anticipate and mitigate the effects of climate change on vector-borne disease transmission. This review underscores the urgency of addressing climate change as a critical component of global health initiatives and the importance of interdisciplinary approaches in tackling this complex issue.
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Wild rodent communities represent ideal systems to study pathogens and parasites shared among sympatric species. Such studies are useful in the investigation of eco-epidemiological dynamics, improving disease management strategies and reducing zoonotic risk. The aim of this study was to investigate pathogen and parasites shared among rodent species (multi-host community) in West Wales in an area where human/wildlife disease risk was not previously assessed. West Wales is predominantly rural, with human settlements located alongside to grazing areas and semi-natural landscapes, creating a critical human-livestock-wildlife interface. Ground-dwelling wild rodent communities in Wales were live-trapped and biological samples – faeces and ectoparasites – collected and screened for a suite of pathogens and parasites that differ in types of transmission and ecology. Faecal samples were examined to detect Herpesvirus, Escherichia coli, and Mycobacterium microti. Ticks and fleas were collected, identified to species based on morphology and genetic barcodes, and then screened for Anaplasma phagocytophilum, Babesia microti, Borrelia burgdorferi sensu lato, and Bartonella sp. All the pathogens and parasites screened pose a characteristic epidemiological challenge, such as variable level of generalism, unknown zoonotic potential, and lack of data. The results showed that the bank vole Myodes glareolus had the highest prevalence of all pathogens and parasites. Higher flea species diversity was detected than in previous studies, and at least two Bartonella species were found circulating, one of which has not previously been detected in the UK. These key findings offer new insights into the distribution of selected pathogen and parasites and subsequent zoonotic risk, and provide new baselines and perspectives for further eco-epidemiological research.
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This is a rapid protocol proposed after its prolonged usage for the clearing, staining, and mounting of the medically important hematophagous ectoparasites obtained from human and small mammals collected in Tamil Nadu and Kerala, India. During the biodiversity study on ectoparasites, this altered protocol improved significantly the visibility of the major essential taxonomic key characters present on the minute body of the uncharacterized chigger mites, fleas, and lice viewed under phase-contrast microscopy for identification. This modified method will be enormously useful for imparting training, teaching, and research on acarology.
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Fleas are hematophagous insects infesting mainly small mammals and, less frequently, birds. With their wide range of potential hosts, fleas play a significant role in the circulation of pathogens in nature. Depending on the species, they can be vectors for viruses, bacteria, rickettsiae, and protozoa and a host for some larval forms of tapeworm species. The aim of this study was to determine the species composition of fleas and their small rodent host preferences in eastern Poland. Animals were captured in traps in various types of ecological habitats (a site covered by grassland vegetation within city limits, an unused agricultural meadow, and a fallow land near a mixed forest). The following rodent species were caught: Apodemus agrarius, Apodemus flavicollis, Microtus arvalis, and Myodes glareolus. Additionally, Ctenophthalmus agyrtes, Ctenophthalmus assimilis, Hystrichopsylla talpae, and Nosopsyllus fasciatus flea species were identified. The peak of the flea activity was noted in summer months. C. agyrtes was found to be the most abundant flea species in eastern Poland, while the greatest numbers of fleas were collected from the rodent species A. agrarius.
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Sylvatic plague, caused by the bacterium Yersinia pestis and transmitted by fleas, occurs in prairie dogs of the western United States. Outbreaks can devastate prairie dog communities, often causing nearly 100% mortality. Three competent flea vectors, prairie dog specialists Oropsylla hirsuta and O. tuberculata, and generalist Pulex simulans, are found on prairie dogs and in their burrows. Fleas are affected by climate, which varies across the range of black‐tailed prairie dogs (Cynomys ludovicianus), but these effects may be ameliorated somewhat due to the burrowing habits of prairie dogs. Our goal was to assess how temperature and precipitation affect off‐host flea abundance and whether relative flea abundance varied across the range of black‐tailed prairie dogs. Flea abundance was measured by swabbing 300 prairie dog burrows at six widely distributed sites in early and late summer of 2016 and 2017. Relative abundance of flea species varied among sites and sampling sessions. Flea abundance and prevalence increased with monthly mean high temperature and declined with higher winter precipitation. Predicted climate change in North America will likely influence flea abundance and distribution, thereby impacting plague dynamics in prairie dog colonies.
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Rodent-borne diseases such as bubonic plague remain a significant threat to public health in tropical countries. In plague-endemic areas, little information exists on the factors triggering periodic bursts, thus rendering preparedness strategies for preventing the negative impacts of the deadly zoonosis difficult. In this study, we assessed how species richness, diversity, and community structure of rodents are associated with plague persistence in Mbulu District, Tanzania. Rodent data were collected using the removal trapping technique. We captured 610 rodents belonging to 12 species, with Mastomys natalensis recording highest abundance. There was significantly higher abundance and species richness in persistent than non-persistent plague locality. Also, house premises recorded significantly lower species richness than farm and forest habitats. Additionally, we found three broad rodent community structures that varied significantly between studied habitat types suggesting high rodent populations interaction at fine-scale resource abundance. The high abundance and diversity of plague-susceptible rodent reservoirs suggestively contribute to the plague persistence in the foci. These results may be useful to developing preparedness strategies in these areas to control plague outbreaks.
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Background Rodents are known to be reservoirs of plague bacteria, Yesinia pestis in the sylvatic cycle. A preliminary investigation of the suspected plague outbreak was conducted in Madunga Ward, Babati District Council in Manyara Region December-2019-January 2020 Following reported two cases which were clinically suspected as showing plague disease symptoms. Method The commensal and field rodents were live trapped using Sherman traps in Madunga Ward, where plague suspect cases were reported and, in the Nou-forest reserve areas at Madunga Ward, Babati District Council, to assess plague risk in the area. Fleas were collected inside the houses using light traps and on the rodents ‘body after anaesthetizing the captured rodent to determine flea indices which are used to estimate the risk of plague transmission. Lung impression smears were made from sacrificed rodents to examine for possible bipolar stained Yersinia spp bacilli. Results A total of 86 rodents consisting of ten rodent species were captured and identified from the study sites. Nine forest rodent species were collected. Field/fallow rodent species were dominated by Mastomys natalensis. whereas domestic rodent species captured was Rattus rattus. Overall lung impression smear showed bipolar stain were 14 (16.28%) while House Flea Index (HFI) was 3.1 and Rodent Flea Index (RFI) was 1.8. Conclusion The findings of this study have shown that, the presence of bipolar stained bacilli in lung impression smears of captured species of rodents indicates (not confirmed) possible circulation of Yesrsinia pests in rodents and the high flea indices in the area which included the most common flea species known to be plague vectors in Tanzania could have played transmission role in this suspected outbreak. The study recommends surveillance follow-up in the area and subject collected samples to the standard plague confirmatory diagnosis.