2021.06.02.19
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A Spatio-temporal distribution analysis of vesicular stomatitis outbreak in Ecuador, 2018

María Teresa Salinas1, Euclides José De La Torre2,
Paola Katerine Moreno3, Andrés Alejandro Vaca4 and Rubén
Alexander Maldonado5*
Available from: http://dx.doi.org/10.21931/RB/2021.06.02.19 (registering DOI)
ABSTRACT
Vesicular
stomatitis (VS) is a viral disease primarily affecting cattle, swine, and
equine causing economic losses. It is of particular interest because its
outward signs are similar to those of foot-and-mouth disease. Outbreaks of VS
occurred in several herds in Ecuador in 2018, affecting principally bovines. In
this sense, the present study was conducted to characterize the temporal and
spatial dynamics of Vesicular stomatitis occurrence between January and
December 2018. During the study period, 583 animals with symptoms of VS were
reported. In this way, tissue samples were collected, VS was diagnosed, and
outbreaks were defined as herds with a confirmed positive test for the disease.
Outbreaks
were georeferenced, and Space-time clusters were used to determine zones where
the number of reported outbreaks was more significant than expected. A
space-time permutation scan statistic (STPSS) was used to identify hot spots of
space-time interaction within patterns of the cases reported. Standard Monte
Carlo Critical Value was used to test for the cluster's significance. A total
of 399 outbreaks were presented in 18 provinces. Spatial scan statistics
allowed the detection of four significant space-time clusters of VS outbreaks.
The highest incidence was reported around week 35 and week 44, which were
observed outbreaks increase in the country's north region. In this sense,
clusters coincided with the areas with the highest incidence of outbreaks. Besides,
maps showed places where the disease is not shared. The information showed in
the present study may contribute to prevents VS spread into regions of Ecuador
that is only sporadically affected by the disease. Monitoring in affected zones
may lead to quick responses to possible outbreaks issuing alerts when there is
a greater than typical risk of spreading the disease.
Keywords:
Spatio-temporal analysis, outbreak, vesicular stomatitis virus.
INTRODUCTION
Spatio-temporal
is a type of clustering in which data values, including the time dimension, are
introduced into spatial data. Accordingly, the objects are grouped as per their
spatial and temporal similarity1. Vesicular
stomatitis (VS) is a disease of livestock commonly observed in adult animals caused
by vesicular stomatitis virus (VSV) belonging to Rhabdoviridae, genera Lyssavirus
and Vesiculovirus.2 3 VSV
affects cattle, swine, and equine. However, it also can affect sheep, goats,
camelids, and buffalo. Natural infection in sheep and goats is rare but has been
demonstrated in experimental conditions. The incubation period is between 2 to
8 days. The morbidity rate varies from 5 up to 90 percent.4 How VS
spreads is not fully understood; once the disease is introduced into a herd, it
may move from animal to animal. VSV's can spread quickly under natural
conditions. The most common transmission routes are vector-borne, direct
contact, or exposure to saliva or fluid from ruptured vesicles.5 However, the
virus can infect animals by the transcutaneous or transmucosal route.6 VSV has an
important economic impact resulting in quarantine, animal movement
restrictions, and decreases in meat and milk production.7 Also, VSV
denotes extensive regulatory responses by government agencies, including trade
restrictions and market closures.8 For this
reason, it has become a disease of interest. Its clinical signs are similar to
those of foot-and-mouth disease, vesicular exanthema of swine, or swine
vesicular disease. However, generally less severe.9 10 There are
two serotypes of VSV, Vesicular stomatitis New Jersey (VSV-NJ) and Vesicular
stomatitis Indiana (VSV-IND). Both serotypes have similar morphological
characteristics and pathology with the difference of the neutralizing antibodies
generation in infected animals.11 Indiana
serotype is subtyped serologically into 3 groups. VSV-IND belongs to the
Indiana 1 subtype, Cocal virus to the Indiana 2 subtype, and VSV-AV to Indiana
3. Deaths are sporadic in cattle and horses, but higher mortality is observed
with VSV-NJ infection in swine.12 Confirmed
VSV infection is limited to the Americas. The virus is thought to have
originated in equatorial America and spread north during two separate
colonizing events3. This disease is seasonal, although cases may
occur throughout the year. Outbreaks caused by VSV-NJ or VSV-IND usually occur
each year. They are particularly common at the end of the rainy season or early
in the dry season. In endemic areas, both explosive epidemics and outbreaks of
slow dissemination can be seen with a relatively small number of cases.11 Specifically,
VSV-NJ and IND-1 are endemic in Ecuador and other countries in South America.3
The samples used for diagnosis include vesicle fluid, epithelium covering
unruptured vesicles, or epithelial flaps of freshly ruptured vesicles. Recommended
tests by World Organization for Animal Health for vesicular stomatitis include
IS-ELISA (Indirect Sandwich), CFT (Complement Fixation test), RT-PCR (Reverse
transcriptase-polymerase chain reaction), LP-ELISA (liquid phase blocking
ELISA), c-ELISA (competitive ELISA), and V.N. (virus neutralization)13. In 2018,
an outbreak of Vesicular stomatitis in Ecuador occurred. The outbreaks
distribution included 18 provinces in which different livestock premises were
investigated. Therefore, this study aimed to characterize the temporal-spatial
distribution of Vesicular stomatitis outbreaks reported in Ecuador in 2018.
METHODS
Animal samples – Tissue
samples (vesicles or lesions on the inner surfaces of the foot, lips, tongue,
udder, gums, and dental pad) (n=583) were collected by field technicians as
information about the suspected animals. VS was diagnosed through IS-ELISA Differential Typing Kit (PANAFTOSA-OPAS/OMS)
(n=568). Molecular diagnosis (n=15) was performed using Transcriptor First Strand cDNA Synthesis Kit (Roche) and GoTaq® Hot Start Green Master Mix (Promega
Corporation). The diagnosis was performed at the Animal Diagnosis Laboratories
at Agrocalidad.
Data collection – Information
and laboratory results corresponding to all livestock premises attended for VS
between January and December 2018 were registered in databases. The information
registered for each outbreak included: identification of cases and samples,
date of the case reported, animal species, livestock premise activity,
geographic location, number of samples collected, and diagnosis results.
Outbreak information – Outbreaks
were assumed to have started on the date when clinical signs compatible with VS
were first observed in the herd and were notified to the agency. Cases were
defined as animals with compatible clinical signs of VS. Outbreaks were defined as herds with at least 1 animal with a
confirmed positive test result for VSV. Livestock premises, where results were
negative for testing, were considered negative for VSV infection. Cases were
aggregated into 7-day groups to account for week variations. These variations
were based on calendar week. Each outbreak was georeferenced using the
geographic coordinates of the herd and QGIS software. To analyze outbreaks,
these were georeferenced by use of the centroid of the municipalities. The
centroid data were obtained from databases of the Instituto Geografico Militar
- IGM. Outbreaks caused by VSV-NJ and VSV-IND were used in the analyses
reported here.
Data analysis and Spatio-temporal distribution - The
space-time was analyzed using SaTScan software, in which the number of cases
was compared to the expected cases of outbreaks within each cluster. Outbreaks
were mapped using the same software. Space-time clusters were used to determine
zones where the number of reported outbreaks was more significant than expected
based on the population size. A space-time permutation scan statistic (STPSS)
was used to identify hot spots of space-time interaction within patterns of the
cases reported. In this sense, a retrospective Space-Time analysis was used for
clusters with high rates. Standard Monte Carlo Critical Value was used to test
for the cluster's significance. The clusters were determined as statistically
significant when its test statistic was greater than the critical value, which
is the significance level (P<0.001).
RESULTS
Cases
started from January 5th through December 19th, 2018. During this period, 583
cases from different livestock premises were reported to Agrocalidad in
different provinces. Cases were presented as follows: 561 cattle, 11 equines, 8
swine, and 3 caprines. From the total presented cases, 399 (68.44%) were
confirmed outbreaks with VS. In this regard, about 60% of the reported cases
were confirmed outbreaks. There was an increase in the number of outbreaks
starting in August that continued through November. Outbreaks were present in
three regions of Ecuador (Highlands, Coast, and Amazon). Bovines were the most
affected with 391 (98.00%) outbreaks, followed by 5 (1.25%), 2 (0.50%), and 1
(0.25%) outbreaks in swine, equines, and caprines, respectively. Outbreaks were
presented in 18 provinces. Consequently, Santo Domingo was the province with
the highest number of outbreaks, presenting 93 (23.31%) outbreaks to VS,
followed by Imbabura 75 (18,80%) and Napo 65 (16.29%). The remaining 184
(31.56%) cases were confirmed as a negative for VS. Furthermore, Santo Domingo
de Los Tsáchilas presented outbreaks in 61.11% of its municipalities, followed
by Imbabura (57.14%), Pastaza (47.62%), and Napo (39.13%). The distribution and
the total outbreaks per province and municipalities are detailed in Table 1, in
which the distribution of outbreaks by quarter can be observed. Thereby it is
possible to visualize the months that arose a significant increment thereof. For
a better appreciation, the outbreaks distributed by quarters are shown in
Figure 1. From 399 outbreaks, 372 (93.23%) belong to VSV-NJ, 22 (5.52%) belong
to VSV-IND, and 5 (1.25%) presented results for both virus serotypes. The serotype
which had prevailed for most of the provinces during the outbreak was VSV-NJ.
For the other hand, VSV-IND serotype was located in Morona Santiago, Pastaza,
Orellana, Sucumbíos, Zamora Chinchipe, Pichincha, Santo Domingo de Los
Tsáchilas, Esmeraldas and Guayas provinces. The distribution map of the serotypes
is shown in Figure 2. Heat maps (Figure 3) were provided by the Directorate of
Zoosanitary Surveillance of Agrocalidad and represent the alert notifications
for vesicular diseases; this means that vesicular stomatitis and other diseases
are included in the maps. Thus, heat maps show the distribution of alert
notifications of vesicular diseases presented in 2017 and 2018. There was an
increase in the number of outbreaks starting in August (Week 31) that continued
through the last week of November; in this period, 509 cases were reported of
which 351 outbreaks were confirmed. After week 37 of the recorded outbreaks, it
went 2 weeks before new outbreaks were recorded, and after that, it was never
more than 1 week between a recorded outbreak and another recorded
outbreak. The highest incidence was
reported in week 44, in which 76 outbreaks from 114 cases were confirmed
(Figure 4). Spatial scan statistics allowed the detection of four significant space-time clusters (P < 0.001) of VS
outbreaks (Table 2). The circular base represents the significant clusters
corresponding to the outbreaks' geographical area (Figure 5).

Table 1 - Distribution of outbreaks of Vesicular
stomatitis per municipality confirmed in Ecuador in 2018.

Figure 1. Distribution by quarters of outbreaks of Vesicular stomatitis confirmed
in Ecuador in 2018.

Figure 2. Distribution by serotype of outbreaks of Vesicular stomatitis confirmed
in Ecuador in 2018.

Figure 3. Heat maps of alert notifications for
vesicular diseases in 2017 (3a) and 2018 (3b).

Figure 4. Weekly incidence of VS in Ecuador in 2018. Positive
(blue) and negative cases (red).

a Simulated p-value, calculated
with 999 Monte Carlo replications.
Table 2 - Geographic
Analysis of Vesicular Stomatitis Rates, using the Space-time Statistic: Ecuador,
2018.

Figure 5. Spatial distribution of outbreaks of Vesicular stomatitis confirmed in
Ecuador in 2018.
DISCUSSION
Due
to the increase of vesicular stomatitis outbreaks presented during 2018 in
Ecuador, this study analyzed the reported cases. Our approach through
Spatio-temporal analysis enabled us to determine the sites of the outbreaks
which have epidemiological importance. Literature mention that space-time scan
statistics allow identifying statistically significant hotspots. The hotspots
are evaluated by a significance value1 and are helpful for pattern
understanding14. In this
manner, the space-time scan statistic of this study identified the locations of
the most-significant clusters.
Consequently,
these clusters coincided with the areas with the highest incidence of the
outbreaks. Thus, the study revealed that the increase in VS outbreaks reported
during 2018, compared with cases in 2017, was associated with four significant
space-time clusters. Some of the outbreaks were not included in any of the
fourth clusters; this is due to common cases filed each year and are not
representative.
The
highest incidence was reported around week 35 and week 44, which were observed
outbreaks increase in the country's north region (Figure 3). In this sense, the
cluster closes to the municipality of Ibarra indicated the highest incidence
rate, suggesting that the rate of transmission between herds was higher within
this area than the other clusters in which the rate was similar. It was also
observed that outbreaks increase began at the end of the summer or dry season
and the beginning of the rainy season. This observation matches a monitoring
study in Costa Rica in which all episodes of disease occurred at the beginning
of the dry season15. Another
study mention that VS outbreaks incidence from year to year varies according to
the region. For example, in frostless areas, the disease is encountered every
year16.
Factors
that caused outbreaks still are not determined; however, studies suggest climate
change may have favored the increase of vectors in affected areas, promoting disease
transmission. A study in Mexico suggested that a change in climatic conditions
could favor the vectors' spread into areas in which they are usually absent.17 Also,
another study indicates an apparent relationship between climatic zones and the
frequency of occurrence of vesicular stomatitis. However, it appears that
limitations are imposed on the spread of the disease by particular physical
features of the land or by habitat conditions within these zones16. Environmental
conditions and climate variables play an essential role in the dynamics,
distribution, and transmission of vector-borne diseases. In this way, when
compared with previous years, it is possible to notice a change that triggered
the outbreaks, suggesting that environmental and epidemiological factors may
have influenced VSV spread. Even when the heat maps group all the vesicular
disease alert notifications, it can be appreciated a difference in the
distribution of cases between 2017 and 2018. In this manner, in the 2018 map,
it can be seen an increment in the number of cases compared to the 2017 map,
which represents the average number of alert notifications in provinces for
each year. Likewise, the 2018 map shows places where the disease is not shared.
South
and Central America have ecologic niches where outbreaks appear annually. The
prevalence of the virus is established in the places where the disease is
constantly being enzootic in those areas.18 For
instance, Costa Rica presents two zones where the virus's activity is high
considerably, one is located in the highlands (premontane tropical forest), and
another is located in the lowlands (tropical dry forest)19. Ecuador
also shows enzootic zones for VS, it is so every year common cases are
presented in provinces like Carchi, Guayas, Manabí, Pichincha, Loja, Los Ríos
and Zamora Chinchipe. Moreover, the disease has repeatedly spread along
waterways in certain zones in the USA. Woodland pastures, rivers, and lakes are
common in most epizootic regions and absent in the regions where the disease is
self-limiting16. In this
way, water bodies in the country, in conjunction with environmental factors,
could have been another factor of the spread of the virus. Additionally, increased
attack rates in pastured animals suggest insect vectors' role in the
transmission of VSV20.
Investigations reports VSV transmission routes involve insect vectors, such as
mosquitoes, sand flies21,
22, black
flies, and biting midges. In this way, VSV has been isolated from multiple
arthropods collected in enzootic areas and during epizootics. Similarly, they have
been found in high abundance, vectors causing agricultural pests like black
flies and Culicoides midges when
outbreaks occur5. In
Ecuador has been found sand flies in some provinces (Azuay, El Oro, Esmeraldas,
Guayas, Morona Santiago, Pastaza, Pichincha, Sucumbíos, and Zamora Chinchipe)23, being
places that coincide with the presence of VS cases, so, the presence of vectors
could have been a factor for the spread of the virus in the country.
Many
places in South America are considered endemic zones for VSV, such as
northeastern and northern Brazil24. In 1986,
Ecuador recognized Loja province as an endemic area for VSV- N.J. Guayas, Los
Rios, and Pichincha are recognized as endemic zones for VSV- N.J. at a low
level, and Manabí, Cotopaxi, El Oro, and Zamora Chinchipe are considered as
endemic zones at an occasional level. For VSV-I, there is not a specific place
in Ecuador considered as an endemic, but it constantly appears in Loja, Zamora
Chinchipe, Guayas, and Pichincha25. This is
consistent with the distribution of VSV-NJ and VSV-I serotypes in Ecuador
during the cases filed in 2018. However, the VSV-I serotype was found also in
Esmeraldas, Santo Domingo de Los Tsáchilas, Sucumbíos, Orellana, Pastaza, and
Morona Santiago.
The
comparison with the distribution of the virus of previous years could help
found an association of the expected virus each year and the virus found in new
places.
CONCLUSIONS
Comprehend
the temporal-spatial distribution is key to understanding VS epidemiology and improving
and enforcing the responses of outbreaks when it appears, taking with regard
that vesicular stomatitis presents similar symptoms with foot and mouth disease
considered as a significant disease into animal health, economy, and business
relationships. Viewed in this way, knowing the places where the farms are
affected by the disease seasonally allows the prevention and control of the
virus. For instance, in the USA, the outbreaks appear in intervals of 10 years
in which the losses are estimated at around $200 per individual and around
$15.565 per farm with the virus5. Further
studies about vesicular stomatitis and its epidemiology will help better
understand the disease and its behavior to changes that may cause new
outbreaks. Accordingly, processes of regulation, control, and animal health
surveillance headed to maintain the sanitary status in Ecuador could be
supported based on the present study results. Monitoring in affected zones may
lead to quick responses to possible outbreaks issuing alerts when there is a
greater than typical risk of spreading the disease, in areas that are not
affected by the disease, or present minimal cases that are expected every year.
Acknowledgments
We
acknowledge field technicians of the Agencia de Regulación y Control Fito y
Zoosanitario – Agrocalidad. They attend case notifications in the different Ecuador
and Animal Health Coordination provinces because they manage animal health
processes to increase animal health standards in the country.
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Received: 12 December
2020
Accepted: 22 February 2021
María Teresa Salinas1, Euclides José De La Torre2, Paola
Katerine Moreno3, Andrés Alejandro Vaca4 and Rubén
Alexander Maldonado5*
1 Laboratorio de Virología. Agencia
de Regulación y Control Fito y Zoosanitario – Agrocalidad. Av. Eloy Alfaro y
Federico González Suárez, Tumbaco, Pichincha, Ecuador
2 Dirección
de Diagnóstico Animal. Agencia de Regulación y Control Fito y Zoosanitario –
Agrocalidad. Av. Eloy Alfaro y Federico González Suárez, Tumbaco, Pichincha,
Ecuador
3 Dirección
de Control Zoosanitario. Agencia de Regulación y Control Fito y Zoosanitario –
Agrocalidad. Av. Eloy Alfaro y Federico González Suárez, Tumbaco, Pichincha,
Ecuador
4 Dirección
de Control Zoosanitario. Agencia de Regulación y Control Fito y Zoosanitario –
Agrocalidad. Av. Eloy Alfaro y Federico González Suárez, Tumbaco, Pichincha,
Ecuador
5
Laboratorio de Cultivo Celular. Agencia de Regulación y Control Fito y
Zoosanitario – Agrocalidad. Av. Eloy Alfaro y Federico González Suárez,
Tumbaco, Pichincha, Ecuador
Corresponding
author: Rubén Alexander Maldonado ruben.maldonado@agrocalidad.gob.ec