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\title{Modern building structures are a landscape-level driver of
bat-human exposure risk in Kenya}



\author[1]{Tamika J. Lunn}%
\author[1]{Reilly T. Jackson}%
\author[1]{Paul W. Webala}%
\author[1]{Joseph Ogola}%
\author[1]{Kristian M. Forbes}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\textbf{Abstract}

Identifying the areas and drivers of high-risk interfaces for
human-wildlife interaction is crucial for managing and reversing human
zoonotic disease risk. We suggest that continent-wide improvement to
African housing is inadvertently creating roosting habitat for
synanthropic free-tailed bats (family Molossidae), and opportunity for
human exposure to bat-associated pathogens. We mapped building use by
free-tailed bats from 1,109 buildings along a residential gradient in
rural south-eastern Kenya where viruses of concern have been detected.
We show that bats frequently roost in human-occupied buildings; almost
one-in-ten buildings showed evidence of bat occupation (9.2\%), and
one-in-13 were active roosts (7.6\%). We identified modern-build style
and triangular roofing as building-level predictors of bat occupation,
and the proportion of modern buildings as a landscape-level predictor of
bat occupancy. Given the international focus on building improvement in
Africa, and the increasing access to improved housing already reported
in the literature, we suggest that this is a rapidly accelerating
exposure interface that needs urgent attention and investment. Ethical
pre-emptive exclusion of bats (by sealing bat entrance points) and
restoration of natural roosting habitats should be prioritized as One
Health land-use planning strategies in rural Africa.~

\textbf{Introduction}

The emergence and re-emergence of zoonotic disease is driven by
ecosystem changes at the landscape level \textsuperscript{1}. Ecosystem
disturbances through anthropogenic land use changes have been key
drivers of emerging infectious diseases over the last century
\textsuperscript{2}. Changes to ecosystem features -- such as wildlife
abundance, community composition, demography, behaviour, movement,
contact patterns, and pathogen susceptibility -- directly and indirectly
alter the risk of pathogen transmission from wildlife to humans, through
modifying disease dynamics within wildlife hosts and contact between
wildlife and humans\textsuperscript{1}. Because spatial overlap between
wildlife reservoirs and humans is a key requirement for cross-species
transmission (spillover), studies that investigate how human activities
increase exposure to wildlife are critical for mitigating the
transmission and emergence of zoonoses \textsuperscript{3}.

Urbanisation commonly results in destruction and fragmentation of
wildlife habitat, with ensuing encroachment creating human-wildlife
interfaces at the edges of anthropogenic areas. For synanthropic
wildlife, urbanisation can additionally create habitat and increase key
resources, creating mosaics of human-wildlife interfaces within
anthropogenic areas. Human pathogen exposure from synanthropic wildlife
has been observed for various zoonoses, including tick-borne bacterial
pathogens and viral infections (e.g., McFarlane et al. 2012; Berm\selectlanguage{ngerman}údez et
al. 2016; Bermúdez et al. 2017). Identifying the specific drivers of
these high-risk interfaces is especially important in global hotspots
for emerging infectious diseases \textsuperscript{7,8}, countries with
limited resources for disease surveillance, prevention and
control\textsuperscript{7}, and for taxonomic groups identified to
harbour zoonotic pathogens \textsuperscript{9}. However, information on
wildlife-human exposure remains limited for many under-resourced disease
hotspots, particularly in sub-Saharan Africa and parts of Asia, as well
as for many host taxa, including bats. These deficiencies are
exacerbated by limited understanding of basic bat ecology in remote
parts of Africa and Asia \textsuperscript{10}.

African molossid bats, or free-tailed bats, are some of the most widely
distributed and abundant bats on the African
continent\textsuperscript{11}. Several Molossid species host
zoonoses-associated viral families, including corona-, filo-, paramyxo-,
rota-, astro-, flavi-, and lyssaviruses\textsuperscript{12--17}. Two
Molossid species (\emph{Mops condylurus}and \emph{Mops pumilus} ) are
also putative ebolavirus hosts, both showing evidence of infection in
the wild, and the ability to replicate ebolaviruses without morbidity
following experimental inoculation\textsuperscript{18--20}.

Synanthropic free-tailed bat species are increasingly using human-built
structures as roosts, instead of natural roosts in tree hollows and rock
crevasses \textsuperscript{21}. Continent-wide changes to African
housing have seen human dwellings change from traditional buildings with
natural materials (e.g., mud walls and thatch roofs), to modern-style
buildings with finished materials and modern design elements, including
structural beams and ceilings\textsuperscript{22}. Spaces in ceilings,
and between beams and walls, create roosting habitat for free-tailed
bats, and appear to sustain larger colonies than natural roosts and
traditional buildings (up to thousands in modern housing)
\textsuperscript{23}. Changing patterns of bat-bat and bat-human contact
through the use of these anthropogenic structures creates an exposure
interface that may increase pathogen transmission, both among bat
species and from bats to humans.

Given the limited information available on basic bat ecology and
wildlife-human exposure in remote parts of Africa, particularly at
landscape scales, this study aimed to: 1) map high-risk interfaces of
bat-human exposure along a residential gradient in rural south-eastern
Kenya, and 2) to identify building- and landscape-level attributes of
bat-human exposure risk. This study provides empirical information on
the roosting of anthropogenic free-tailed bats in south-eastern Kenya,
and describes the conditions in which housing improvement (without
proper consideration of local bat ecology) could facilitate the
emergence of zoonotic disease in remote parts of Africa. This
information is critical to better understand bat-virus exposure
interfaces that drive disease risk, and to inform strategies for One
Health land-use planning in changing landscapes.

\textbf{Results}

We directly assessed occupation by synanthropic free-tailed bats for
1,014 buildings (checked for signs, sighting and/or audio confirmation,
or discussed occupation with owner) (Figure 1). Of these 1,014
buildings, 93 showed evidence of free-tailed bat occupation and were
included in building- and landscape-level analyses of bat building use.
We recorded the building and roof structure for an additional 95
buildings which could not be accessed directly (1,109 buildings total)
(Figure 2). With evidence weighted to better reflect active roosts
(Appendix S1), 84 out of the total 1,109 buildings surveyed were
considered presently active (occupation category \textgreater{}=4) and
included in landscape-level analyses of bat-human exposure risk. Lines
of evidence for free-tailed and other bat occupation are given in
Appendix S2.

Modern-build style and triangular roofing were identified as
building-level attributes of synanthropic free-tailed bat occupancy
(modern build style: coef= 1.36 ± 0.29, p\textless{}0.0001; triangular
roofing: coef= 2.17 ± 0.37, p\textless{}0.0001). At the landscape level,
building availability and the proportion that were of modern-build --
but not the proportion with triangular roofing -- drove the number of
buildings occupied by free-tailed bats (total number of buildings: coef=
0.007 ± 0.002, p=0.0008; proportion of modern-builds: coef= 0.012 ±
0.006, p=0.030; proportion with triangular roofing: coef= -0.004 ±
0.007, p= 0.540).

This positive association remained when the more stringent assessment of
building occupancy was applied to capture roosts very likely to be
actively occupied (occupation category \textgreater{}=4) (total number
of buildings: coef= 0.005 ± 0.002, p=0.001; proportion of modern-builds:
coef= 0.015 ± 0.006, p=0.017; proportion with triangular roofing: coef=
-0.005 ± 0.008, p= 0.521, Figure 3). In both datasets, the effect of
building number was less than half of the effect from the availability
of modern buildings.

The average building-roost density of roosts considered to be actively
occupied, was 8.4 occupied buildings per km\textsuperscript{2} (range
2-24 per km\textsuperscript{2}), estimated using a traditional measure
of density, or 8.2 occupied buildings per km\textsuperscript{2} (range
2-21.7 per km\textsuperscript{2}) estimated as a kernel density (Figure
4).

Given specific interest in the transition from traditional- to
modern-style housing, all analyses were repeated on a subset of data
that included traditional- and modern-style houses only, and houses with
triangle and flat roofing only (i.e., with structures including
latrines, livestock coupes, and greenhouses removed, leaving 806
buildings total). Model results were not substantially or directionally
different in the sensitivity analysis (Appendix S3), though
proportionally more houses were occupied (one-in-seven with evidence of
occupation, 13.1\%, and with nearly one-in-ten being active roosts,
10.4\%).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1: Map of study sites. Central panel shows the distribution of
study sites in the Taita-Taveta county, south-eastern Kenya. Note that
sites were distributed across low-lying areas only, as synanthropic
free-tailed bats do not occur at higher elevations of the county
(observable as green cover in the centre, centre-bottom, and right areas
of the satellite image). Small panels show the ten, 1x1 km sites with
roads (black lines) and building footprints (yellow). Building
footprints were obtained from Microsoft (2022), and are based on
satellite imagery collected in 2020 and 2021. Human land-use in this
county spans a gradient of development, from rural areas with
predominantly traditional building practices, to more urbanised areas in
the townships of Mwatate, Maktau and Voi (labelled), with predominantly
modern building practices.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2: Building type and roof design of buildings evaluated in the
survey. We classified modern buildings as those with walls and flooring
built from finished materials (e.g., cement and tiles), and traditional
as those with walls and flooring built from unfinished materials (e.g.,
compacted earth). Modern-style designs often have exposed structural
beams and ceilings, whose spaces create roosting habitat for
synanthropic free-tailed bats. Triangular roofs provide a taller apex
for bat emergence, needed for molossid bats to take flight due to their
wing morphology\textsuperscript{25}. The added height from triangular
roofs also keeps roosting bats out-of-easy-reach from people, and makes
disturbance more difficult.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3: Proportion of occupied buildings relative to the number of
buildings available, and the proportion of buildings that were of modern
build with triangular roofing. Figure shows that sites with higher
proportions of modern buildings have higher occupancy, regardless of
number of available buildings or triangular roofing. Occupancy was
determined using a threshold score of four or more (occupancy is very
likely).\emph{}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 4: Building occupation by bats across the landscape. Distribution
of occupied buildings are shown as filled circles, and unoccupied
buildings as unfilled circles. Occupied building density per
km\textsuperscript{2} is indicated with orange shading. Occupied
building density is estimated as a fixed-bandwidth kernel estimate from
an occupation index of [?]4 (occupation very likely).

\textbf{Discussion}

Continent-wide improvements to African housing have precipitated a
myriad of positive human health outcomes, including reductions in
soil-transmitted helminths, diarrhoeal disease, leishmaniasis, malaria,
and respiratory disease, and improved mental
wellbeing\textsuperscript{22,26}. In this way, house design is integral
to the United Nations Sustainable Development Goal 3: `\emph{ensure
healthy lives and promote well-being for all at all ages} '. We report
an inadvertent and so-far undocumented outcome of housing improvement in
sub-Saharan and rural Africa; that changes to building practices are
simultaneously creating habitat for bats, and potentially increasing
human exposure risk to bat-associated pathogens. Of the 1,109 buildings
surveyed in our study, almost one-in-ten showed evidence of bat
occupation (9.2\%), and one-in-13 were active roosts (7.6\%). We
identified modern-build style and triangular roofing as building-level
predictors of bat occupation, and the proportion of modern buildings as
a landscape-level predictor of bat occupancy. Given the international
focus on building improvement in Africa, and the increasing access to
improved housing already reported in literature \textsuperscript{22}, we
suggest that this is a rapidly accelerating exposure interface that
needs urgent attention and investment.

Synanthropic free-tailed bat species are highly aggregative and use
social cues to locate existing roosts \textsuperscript{27}. Modern-build
structures typically have more spaces for bats to roost and can support
higher densities of individuals. The reported occupation of modern-build
houses possibly reflects a preference in habitat by these bats; roosting
with conspecifics in large roosts, as opposed to roosting separately in
smaller roosts, has several advantages including reduced risk of
predation \textsuperscript{28}, and access to mates during the breeding
season \textsuperscript{29}. It is possible that the removal of natural
habitat, particularly large hollow-bearing trees, could be contributing
to the use of anthropogenic structures, similar to other bat
systems\textsuperscript{30,31}. However, there is insufficient data on
historical and current vegetation in this area to investigate.
Practically, large roosts likely pose a greater risk of exposure to
humans, and a greater burden to residents. Ceiling collapse due to the
weight of accumulated faeces was frequently reported by owners of modern
buildings with ceilings containing large numbers of bats, for instance.

Not all modern structures that were available were occupied. This may be
partly associated with building-level nuances not captured in this
dataset, such as successful blockage of roost access points by owners,
or recent bat eviction efforts. Alternatively, this may indicate that
availability of ideal refugia is not a limiting factor in bat
occupation, and instead, that landscape patterns in building use are
driven by the presence of at least a few ideal habitats in which animals
can aggregate. Speculatively, this could indicate that synanthropic
free-tailed bat occupation is unlikely to saturate available buildings
beyond a certain threshold of availability. Baseline information and
continued monitoring of bat roosting would be needed to investigate
this, though the positive association between landscape-level occupancy
and the proportion of modern-style buildings suggests that this
threshold (if it exists) has not been reached.

We caution that bat occupation of housing may be an accelerating
exposure interface. The African continent's population is the fastest
growing in the world, with an estimated increase of 1.3 billion people
expected between 2015 and 2050 \textsuperscript{32}. This growth will
necessitate hundreds of millions of new homes. In addition, shifting
economic and demographic profiles in the continent will continue to
promote access to improved housing. The proportion of houses built with
finished materials increased from 32\% in 2000 to 51\% in 2015, with
hundreds of millions of Africans accessing improved
housing\textsuperscript{22}. These changes present a powerful
opportunity to improve human wellbeing, but only with proper
consideration of local ecological context. Investment in bat- and
human-friendly housing infrastructure is needed to ensure that
vulnerable populations are not left exposed to bats and bat-associated
pathogens. Investment in key areas will also contribute to the global
effort in preventing emerging infectious diseases. African countries are
hotspots for bat species diversity and disease spillover, yet rural and
remote regions of Africa often have limited resources to detect or
combat the first stages of disease emergence after exposure and
spillover \textsuperscript{7,8}. Intervention at exposure interfaces
will help pre-empt spillover of potentially new emerging infectious
diseases, and prevent large-scale emergence in-country or globally.

Housing improvement initiatives should include proper consideration of
local bat ecology to reduce human-bat exposure risk. Individual risk can
be immediately reduced by pre-emptively and thoroughly sealing access
points to bats. This a highly successful mitigation strategy but can be
prohibitively expensive in rural areas \textsuperscript{33}. Depending
on availability and affordability of materials, sealing access points
can also leave design features unfunctional (e.g., sealing ventilation
points and chimneys with wire mesh vs with cement or clay). Improvements
to the availability and affordability of suitable and bat-safe materials
should be made a priority. In addition, the restoration of natural
roosting habitats should be considered as a long-term mechanism for
reversing building use \textsuperscript{34}. This could be achieved by
providing support to existing environmental stewardship programs
involving tree planting (e.g., local groups like the Taita Taveta WCK
Action Group, and broader ACK initiatives) \textsuperscript{35}.

The removal of bats using pesticides or chemicals was frequently
reported by building owners, and/or by blocking entrance points with
thorny plants that get caught in bat wings and cause death. These
approaches are both non-ethical and not effective for long-term
exclusion of bats, as killing bats does not prevent roost
repopulation\textsuperscript{36,37}. Extermination attempts have also
been linked with increased pathogen shedding by bats, and transmission
to humans\textsuperscript{38,39}. Pre-emptive exclusion is the safest
and most ethical approach for limiting bat-human exposure in the
immediate term.

This is the first study to provide empirical estimation on building
roost density of synanthropic free-tailed bats, and describes the
conditions facilitating human-bat exposure in remote parts of Africa.
These results set the foundation for additional research and management
actions to alleviate the risks posed by identified bat-human exposure
interfaces. Surveillance for priority zoonotic pathogens at interfaces
where transmission risks are identified, and the development of
culturally appropriate and locally feasible interventions that can be
used to reduce the risk of contact and transmission at these high-risk
interfaces, should be prioritized for future research and management
action. Analysis of temporal patterns in occupation and/or within-roost
density could also be used to highlight variation in bat exposure risk
within and between years, and prioritise educational efforts on disease
risk and mitigation. Empirical information provided by this study, on
the building-roost density of anthropogenic free-tailed bats, will be
crucial for understanding baseline ecological states for these species,
and could be used for future management efforts for these species. This
information could also be utilised to develop host-virus models to
examine spillover risk now, and under conditions of anthropogenic
change.

\textbf{Methods}

We collected data on synanthropic free-tailed bat building use in the
Taita-Taveta county of south-eastern Kenya (East Africa), between
February and April 2022 (Figure 1). Topography of the county spans
low-lying savannah plains to mountain ranges, with elevations between
700 m (in the plains), up to 2200 m (highest peak of the Taita
Hills)\textsuperscript{40}. Human land-use in this county spans a
gradient of development, from rural areas with predominantly traditional
building practices, to more urbanised areas in the townships of Mwatate,
Maktau, Voi, and Wundanyi, with predominantly modern building practices.
Bat-borne viruses of zoonotic interest have been detected from
free-tailed bats in this area, including coronaviruses and Bombali virus
(genus: \emph{ebolavirus} ) \textsuperscript{41--43}.

We assessed buildings for synanthropic free-tailed bat occupancy within
ten, 1x1 km sites (Figure 1). Sites were chosen to represent the
gradient of human landscapes utilised by free-tailed bats
(traditional-style housing to modern-style housing, Figure 2), and each
was centred on a single building roost identified to contain
synanthropic free-tailed bats. Building footprint maps, derived from
satellite imagery collected in 2020 and 2021, were used to identify all
buildings within sites \textsuperscript{24}. As public attitude towards
bats is negative in this region -- being associated with witchcraft and
witch doctors (Mwasi \& Mwakachola pers. comm.) -- we endeavoured to
become familiarised and trusted by the community prior to surveying
sites and conducted all surveys with a local field assistant.

We individually evaluated each building within our 1
km\textsuperscript{2} sites for occupation by synanthropic free-tailed
bats. To do this, we (1) asked building owners whether they had recently
seen or heard bats inside the building during the day, (2) assessed the
building for signs of bat use (e.g., bat faeces on the ground, stained
ceiling, staining around external roost entrance points, and smell,
Appendix S1), and where possible (3) assessed the building for physical
presence of bats, for sighting and/or auditory confirmation. We noted
features of each building that could impact roosting suitability for
synanthropic free-tailed bats (building type, roof design, and, where
possible, presence of a ceiling) (Figure 2). We classified modern
buildings as those with walls and flooring built from finished materials
(e.g., cement and tiles), and traditional as those built from unfinished
materials (e.g., compacted earth). Buildings were considered occupied
if: the building owners confirmed bat occupation, the building had signs
of bat occupation, or bats were seen or heard inside the building. While
multiple bat species can occupy buildings in this region, synanthropic
free-tailed bats are the most common and are distinctive in their
building use (Appendix S1). Buildings that were occupied by species
other than free-tailed bats were noted, but not included in analyses of
bat building use.

To identify building-level attributes of bat building use, we modelled
the response in building occupation relative to 1) building type (modern
or other), and 2) roof structure (triangular or other). Models were
generalized linear models (GLMs) with maximum likelihood (ML) estimation
and a binomial distribution with a logit-link, fit using the mgcv
package in R. We performed checks of standardised residuals to evaluate
model fit, as per Wood (2017) \textsuperscript{44}. Note that these
indicators of occupation may reflect past or current occupation by
synanthropic free-tailed bats, but nevertheless provide an indication of
building suitability.

To identify landscape-level attributes of bat-human exposure risk, we
modelled response in the number of occupied buildings per site, relative
to 1) the total number of buildings available, 2) the proportion of
those buildings that were a modern-build style, and 3) the proportion of
those buildings with a triangular roof style. To better reflect the
landscape of active roosts (and therefore, the landscape of human
exposure risk), we ran models on an additional dataset where building
occupation was rated based on the collective weight of evidence
indicating current free-tailed bat occupation; 0=very unlikely;
1-2=possible; 3=likely; 4=very likely; 5=certain (Appendix S1). Highly
weighted evidence for occupation included sighting and/or auditory
confirmation of free-tailed bats by the authors (inclusion into category
5, certain of occupation). Moderately weighted evidence for occupation
included owner confirmation of occupation, and signs of occupation.
Low-weighted evidence included building suitability, as per findings
relating to building-level attributes, described above. Buildings were
considered presently occupied if they were categorised as four or
greater (occupation very likely). All levels of evidence were evaluated
in addition to knowledge on where and how many bats were roosting, to
indicate synanthropic free-tailed bats, as detailed in Appendix S1.
Models were fitted as above, but with a Poisson distribution and log
link.

To provide an empirical estimate on landscape-scale building-roost
density, we calculated density as: 1) the total number of occupied
buildings (occupation category \textgreater{}=4) divided by the total
site area, and 2) the average of fixed-bandwidth kernel estimates,
estimated using the spatstat package in R \textsuperscript{45}. Kernel
estimates have the advantage of explicitly incorporating the
distribution of buildings into the density estimate, and can therefore
account for spatial heterogeneity in building
aggregation\textsuperscript{46}. Kernel values were estimated using
roost building location with Gaussian kernel smoothing and a smoothing
bandwidth of 0.3\textsuperscript{47}. Bandwidth was selected by
comparing projected kernel density values to expected density values
based on building distances and survey area. Kernel averages were
calculated per site (pixel size = 0.008969 x 0.00896 meters).

Given the specific interest in the transition from traditional- to
modern-style housing, all analyses were repeated on a subset of data
that included traditional- and modern-style houses only, and houses with
triangle and flat roofing only (Appendix S3).



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\textbf{Acknowledgements} : We thank Peter Mwasi for his assistance in
data collection. We also thank the Taita Environmental Research and
Resource Arc for their logistical assistance, especially Miltone Kimori
and Ken Gicheru. We also acknowledge and thank the Taita people of
Taita-Taveta County for their enthusiasm and participation with this
research.

\textbf{Author Contributions:}

TJL and RTJ conceived the research; TJL designed the research
methodology, led project administration, collected the data, curated the
data, analysed and visualised the data, and drafted the manuscript; PWW
and JO provided resources; KMF acquired funding for the research and
provided supervision; and all authors participated in review and editing
of the manuscript. All authors have read the manuscript, agree that the
work is ready for submission to a journal, and accept responsibility for
the manuscript's contents.

\textbf{Competing Interests statement} : The authors declare that they
have no conflict of interest.

\textbf{Funding} : This study was supported by funding by the Arkansas
Biosciences Institute.

\textbf{Ethical approval} : All applicable institutional and/or national
guidelines for the care and use of animals were followed. Bat fieldwork
was conducted under permits from the National Commission for Science,
Technology and Innovation (\#NACOSTI/P/21/9267), and the Kenya Wildlife
Service (\#KWS/BRM/500 and WRTI/RP/118.6). Ethics approval was granted
by the University of Nairobi Biosafety, Animal use and Ethics committee
(H84/53146/2018), and under Institutional Animal Care and Use Committee
(IACUC) protocol \#22012, granted by the University of Arkansas
Institutional Animal Care and Use Committee. Human ethics approval was
conducted under the University of Arkansas Institutional Review Board
protocol number 2103320918.

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