Spatial Analysis in Areas with High Occurrence of Accidents Caused by Tityus serrulatus and Tityus bahiensis (Scorpiones: Buthidae) in Brazil

Abstract

Introduction

In Brazil, scorpion stings are recorded in high numbers with an increasing epidemiological situation in most municipalities. In the present study, data between 1998 and 2018 in Americana, São Paulo, were analyzed.

Methods

In total, 4122 records on scorpion stings were georeferenced using a Garmin eTREX 30X global positioning system device, with WGS84 datum projection and Universal Transverse Mercator zone 23S. Multiple Poisson regression was used to explore the relationship between the incidence rates of stings and urban planning areas (UPAs). Eight quantitative variables were used to establish the environmental and anthropic characterization of UPAs associated or not associated with scorpionism. A spatial analysis was performed for geoprocessing maps of Americana using spatial statistics tools (optimized hotspot analysis and kernel density function) from cartographic clusters in the ArcMap software, version 10.5.

Results

The optimized hotspot analysis tool identified spatial clusters with high values of the incidence of scorpion stings in the surroundings of all UPAs in the municipality. The estimation of the kernel function of event intensity showed a wide distribution of stings across the area of the entire municipal territory, with UPA-02 and UPA-06 exhibiting the highest occurrence of scorpion stings. Six significant hotspots were established as highest-event-density areas (with occurrences of 160–270) and were contiguous to 4 environmental protection areas, located in more peripheral regions, and to 2 municipal cemeteries, which were located in urban central areas.

Conclusions

This analysis showed that the risk of scorpion stings in different Americana’s UPAs has increased occurrence and incidence intensity.

Keywords

geoprocessing hotspots scorpionism kernel density estimation

Introduction

Scorpionism is a public health problem in various parts of the world. The World Health Organization has categorized it as a neglected tropical disease¹ and speculates that 2.3 billion people are exposed.² Scorpion envenomation has been estimated to have an annual lethality rate of 0.3%, with 1.19 million injured individuals and 3271 deaths.³ The large number of scorpion stings around the world is worrying and indicates the need for new preventive measures and policies to control the incidence and prevalence of these noxious species of scorpions and the morbidity and mortality they cause.⁴

Some geographical distribution patterns of medically significant scorpions in southeastern Brazil are largely associated with the impact of humans on the environment and with several ecological factors characteristic of these species.⁵ Tityus serrulatus is a species that is considered native to the state of Minas Gerais and, over several decades, has opportunistically adapted to synanthropic conditions. New scorpion populations associated with increases in the human population in the southeastern, southern, and central regions of Brazil have also been generated.⁶ This species exhibits successful asexual reproductive strategies for colonization and proliferation in urban areas, and these factors have decisively increased the rates of scorpionism in the state of São Paulo. In recent years, an increased risk of scorpion sting envenomation has been established in the São Paulo metropolitan area and the northeastern region of the state.^7,8 T serrulatus has competed, with higher colonization and dispersal efficiency than Tityus bahiensis (a native sexual species from the same geographic region).⁶

T serrulatus can also be unintentionally introduced to remote and unoccupied territories by human transport, thereby expanding its range. Because of the high prolificacy of the parthenogenetic reproduction strategy of these scorpions, dense populations of these animals can be rapidly established in new localities.⁹ Although most scorpions maintain their home ranges in an ecologically balanced state, T serrulatus has ecological plasticity, which enables it to invade and adapt to colonization processes in urban environments.¹⁰ It is resistant to food and water deprivation, and this tolerance is probably an additional factor underlying the geographical expansion of this species and the difficulties in controlling these animals.¹¹

According to the Brazilian Ministry of Health, scorpionism has great medical importance, with serious epidemiological and economic repercussions. A large number of cases involving venomous animals were reported in Brazil between 2004 and 2018, affecting all 26 Brazilian states and the federal district. Scorpion stings constitute the highest number of notifications in the country, with 167,112 accidents in 2019 and 228 confirmed deaths in 2021 (http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sinannet/cnv/animaisbr.def). The state of Minas Gerais had the most reported cases (and the highest lethality), followed by São Paulo, Bahia, Pernambuco, and Alagoas (which had the highest coefficient of incidence). The coefficient of incidence of scorpion accidents has tripled over the last 10 y. The epidemiology of scorpionism in most Brazilian municipalities has suggested an increasing trend. The risk of scorpion stings has greatly increased in the population, representing a threat to people’s well-being and quality of life.¹²

In the present study, data on the occurrence of scorpion accidents in the municipality of Americana, São Paulo, were analyzed with the aim of determining the spatial distribution of scorpionism in areas with an increased risk of human envenomation. The municipality of Americana has a territory of 133.6 km², of which 92.9 km² is urban, with a population of 237,112 inhabitants, distributed over 10 urban planning areas (UPAs; used as spatial unit of analysis in the study), and a demographic density of 1750 inhabitants/km².¹³

Methods

This study was conducted in accordance with the Normative Instruction 141/2006 and the Normative Instruction 154/2007 of the Brazilian Institute for the Environment and Renewable Natural Resources. It also followed the guidelines of the Brazilian Ministry of Health (ordinance no. 1172/2004 and ordinance no. 1138/2014).

A retrospective analysis was conducted on a 21-y historical series of cases recorded in the Notifiable Diseases Information System (SINAN). Access to SINAN data was authorized by the health surveillance team on “sistema único de saúde” (Unified Health System) and used to search for locations of the occurrences of scorpion stings within urban areas of the municipality between 1998 and 2018. These locations were then georeferenced using a Garmin eTREX 30X global positioning system device, with WGS84 datum and Universal Transverse Mercator zone 23S projection. In the study, 4122 records of scorpion stings were georeferenced, 53 of which were caused by T bahiensis and 4069 by T serrulatus. The respective Universal Transverse Mercator coordinates were organized according to year in Microsoft Excel spreadsheets and added as coordinate data (X, Y) in the ArcGIS software, version 10.5. A moving average graph of annual accidents with scorpions in the analyzed period was prepared in a Microsoft Excel 2016 spreadsheet, which was used to calculate the data trend of the average number of accidents.

Multiple Poisson regression was used to explore the relation between the incidence rates of stings and the UPAs between 1998 and 2018 (10 UPAs, 21 y, 210 observations). The analysis unit for the study was UPA, and the incidence rate of cases was estimated for each UPA per year. All analyses were performed using a significance level of P≤0.05. All significance hypothesis tests and CIs computed were 2 tailed. The analysis was performed using the statistical software R, version 4.1.3.

Specific information was obtained from the municipal institution’s database (department of planning, department of water and sewage, and municipal guard of Americana) on 8 quantitative variables (environmental and anthropic variables) with possible influence on the infestation and dispersion of scorpions and the intercurrence of envenomation. We sought to establish the characterization of UPAs according to environmental variables (green areas and hydrography) and anthropic variables (sewerage system, rainwater network, squares and leisure areas, areas of irregular garbage disposal, recycling and burned-out area foci) associated with scorpionism.

A spatial analysis was performed by plotting geoprocessing maps. Conversion tools were used to obtain classes of layers as resources for shapefiles of the map from the Americana municipality. To build maps, the tools used for converting Keyhole Markup Language (KML and KMZ) files into resource classes and layer files were also used in Google Earth images.

A spatial statistics tool (optimized hotspot analysis) obtained from the mapping cluster routine using ArcMap, version 10.5, was also used to analyze hotspots using minimum input parameters and calculations defined by default. This tool automatically correlated the data on incidence, identified an appropriate analysis scale, and corrected multiple tests and spatial dependence. It also configured the data to determine the best results for the hotspot analysis. Data aggregation from the point to the polygons of its neighborhood was performed, and the z score and P were calculated to detect hotspots and coldspots. A high z score and a low P value for a resource were indicative of a significant hotspot. A low negative z score and a small P value indicated a significant coldspot. The higher (or lower) the z score, the more intense the grouping. A z score close to 0 meant that there was no spatial grouping.

A nonparametric method for the spatial statistics analysis and estimation of density curves (kernel density function) facilitated the calculation of the number of events per unit area. The distribution of events (counting all points within a radius of influence) was transformed into a continuous surface through interpolation.¹⁴ This geoprocessing tool resulted in a plotted output surface on a density raster map (heatmap), thus generating an intensity grid from an influence radius. The density was calculated based on the number of points in a location in which the greater the number of points grouped (cluster) was, the greater was the perception of density. Heatmaps enabled the identification of clusters (hotspots) in areas of great contraction and clustering of points. This enabled the estimation of the intensity of the occurrence of cases by demonstrating the density of the event across the area analyzed.¹⁵ The process has been adjusted by means of a 2-dimensional function applied to the incident events, thereby filtering the variability of a data set from a point-type vector layer¹⁶ and forming a surface of values proportional to the density of samples per unit of endemic area.

Results

The thematic map of scorpion accidents (Figure 1) showed a broad distribution of the occurrence of accidents in the territory, encompassing all the UPAs of the municipality according to incidence rates per 10,000 inhabitants (Table 1). The UPAs with the highest occurrence and incidence of scorpion accidents were UPA-02 and UPA-06. The evolution of the moving average number of scorpion accidents showed an ever-increasing trend between the years of occurrence in the time series (Figure 2).

Figure 1

Thematic map of the incidence rate (scorpion stings per 10,000 inhabitants) in the city of Americana, 1998 to 2018. EPA, environmental protection area; UPA, urban planning area.

Table 1

Occurrence and incidence of scorpion stings by urban planning area

UPA	Inhabitants (n)	Urban area (km²)	Occurrence (accidents)	Incidence (per 10,000)
01	6347	1.7	112	9.4
02	30,124	12.9	618	92.6
03	13,877	14.6	348	52.3
04	35,293	12	618	47.1
05	22,007	16	534	48.7
06	40,642	15.4	681	71.8
07	19,084	4.8	411	30.7
08	20,961	6.6	170	13.5
09	14,015	2.6	183	18.9
10	34,672	6.5	447	71.4

UPA, urban planning area.

Figure 2

Moving average (red line) of annual scorpion stings. Americana, 1998 to 2018.

The geographical characteristics of the UPAs are described in Table 2 and Figure 3. UPAs in Americana cover an average of 9.3 km², with 0.87 km² of green areas, 0.37 km² of squares and leisure areas, 5 recycling units, 55 foci of burned-out areas, and 40 irregular garbage disposal areas on average, and are supported by 0.12 km² of hydrography area, 16 km of rainwater network, and 91 km of sewage network.

Table 2

Characterization of urban planning areas according to variables associated with scorpionism

UPA	Green areas (km²)	Hydrography (km²)	Sewage system (km)	Rainwater network (km)	Squares and leisure areas (km²)	Irregular garbage disposal (areas)	Recycling (units)	Burned-out areas (foci)
01	0.06	0.007	32	4.8	0.06	10	1	14
02	1.5	0.12	108	24.7	0.69	61	5	82
03	2.09	0.28	69	11.7	0.39	32	2	50
04	0.98	0.15	106	21.8	0.53	43	9	68
05	1.05	0.15	152	18.1	0.54	64	4	107
06	2.11	0.38	109	24.7	0.51	85	10	85
07	0.42	0.02	82	12.7	0.31	32	7	55
08	0.14	0.03	85	11.5	0.15	13	1	19
09	0.06	0.003	50	6.7	0.07	12	2	20
10	0.29	0.02	116	23.1	0.43	43	10	49
Mean	0.87	0.12	91	16	0.37	40	5	55
SD	0.81	0.13	35	7.5	0.22	25	3.7	31
Median	0.7	0.08	96	15.4	0.41	38	4.5	53
IQR	0.18 to 1.39	0.02 to 0.15	72 to 109	11.5 to 22.8	0.19 to 0.52	18 to 57	2 to 8.5	27 to 79
Range	0.06 to 2.11	0.003 to 0.381	32 to 152	4.8 to 24.7	0.06 to 0.69	10 to 85	1 to 10	14 to 107

IQR, interquartile range; UPA, urban planning area.

Figure 3

Density distribution of the geographical characteristics of Americana across 10 urban planning areas (1998–2018): area (km²), green areas (km²), hydrography area (km²), sewage network (km), rainwater network (km), squares and leisure areas (km²), irregular garbage disposal (areas), recycling (units), and burned-out areas (foci).

The optimized hotspot analysis tool identified statistically significant spatial groupings of high values (hotspots) and low values (coldspots). The Gi_Bin field classified the data into a range from −3 (coldspot; 99% confidence) to +3 (hotspot; 99% confidence) such that 0 was nonsignificant. Areas marked in red as hotspots were delimited in all UPAs analyzed, thus demonstrating that endemicity and the probable risk of scorpionism were very high (Figure 4).

Figure 4

Optimized map for the analysis of hotspots of scorpion stings in the city of Americana, 1998 to 2018.

The estimation of the kernel intensity function of the event over the analysis period showed that there was a wide distribution of cases across the area covered by the municipality. Six significant hotspots (Figure 5) were established as areas of greater density of events (160–270 accidents) and were contiguous to 4 environmental protection areas, which were located in more peripheral regions, and to 2 municipal cemeteries, which were located in urban areas.

Figure 5

Demonstrative map of the wide distribution of scorpion stings in the city of Americana, using kernel density, 1998 to 2018.

In 2018, the incidence of scorpion stings in Brazil was 75 accidents per 100,000 inhabitants.¹⁷ In the same year, the state of São Paulo recorded 30,476 confirmed cases and 13 deaths, with an incidence of 67 accidents per 100,000 inhabitants.¹⁸ The epidemiological situation in the Americana municipality, state of São Paulo, was very severe, with a rate of 215 scorpion accidents per 10,000 inhabitants, one of the highest incidence rates in the state of São Paulo, with 510 cases (ie, an average of 43±10/mo).

Discussion

Mapping locations that may expose human populations to an elevated risk of scorpion stings can assist public policies and environmental planning through predictive models for the geographical distribution of scorpion species. Thus, mapping may predict regions that carry an increased risk to human inhabitants.¹⁹

This analysis demonstrated and proved the scope of the event in this territory with a high demographic density and a high level of urbanization. The overlap between the human population and a large population of medically significant scorpions, hidden in underground networks with accessibility to urban residential infestation spots, greatly increases the probability of scorpionism. Situations of this nature are characteristic of certain regions of Brazil, Mexico, and northern Africa.²⁰

With regard to the characterization of UPAs with the highest occurrence of scorpion accidents (Table 2), we observed a greater influence of environmental variables related to green areas in UPA-06, UPA-03, and UPA-02 and related to hydrography in UPA-06 and UPA-03. Regarding the anthropic variables, squares and leisure areas in the city were more closely related to the occurrence of scorpionism in UPA-02 because of high human activity in these public places, lack of continual maintenance, and frequent dumping of urban waste. Burned-out areas also influenced the occurrence of scorpion stings because such areas promote the dispersion of scorpions from areas of peripheral forests to the urban, residential environment, which was observed more frequently in UPA-05, UPA-06, and UPA-02. Areas of irregular garbage disposal proved to be influencing factors for scorpion activity in UPA-06, UPA-05, and UPA-02. The sewage system network and rainwater network were correlated with the occurrence of accidents with scorpions in UPA-05, UPA-10, UPA-06, UPA-02, and UPA-04. These networks constitute effective shelter for underground populations of the species T serrulatus and play the role of dispersal and access channels to residential centers throughout Americana. In UPA-10, UPA-06, and UPA-04, the existence of a greater number of units that work with recyclable material, favored access, and shelter conditions for various urban pests, including scorpions, contributed to the risk of accidents with these specimens.

In UPA-03, the death of a 5-y-old child from a scorpion accident was registered in 2013, and in UPA-05, the death of a 3-y-old child was registered in 2017. In UPA-04, the location of the Saudade cemetery and in UPA-06, the existence of the Parque Gramado cemetery were also important factors associated with greater exposure to risk and the existence of higher rates of infestation by scorpions in these urban areas.

Using the hotspot analysis map, it was possible to determine areas with spatial clusters of high occurrences of scorpion accidents. This directed attention to actions for strategic control over urban infestations, which were associated with epidemiological monitoring of health surveillance services and urban pest control (Figure 4).

By constructing density maps using a kernel estimator (Figures 5 and 6), the relationship of scorpionism with various anthropic, environmental, and demographic factors was characterized. This established predictive factors for reducing the number of cases in focal areas with a higher occurrence of scorpion accidents.

Figure 6

Google Earth map showing the spatial distribution of scorpion stings in association with the sewage system and rainwater network in the city of Americana, 1998 to 2018.

Figure 6 clearly showed the close relationship between the spatial distribution of scorpion accidents and the sewage and rainwater networks in the municipality of Americana. This spatial association incorporated this arthropod’s characteristics of having cryptozoic habits and the natural plasticity of an opportunistic, invasive, and colonizing species with adaptive and reproductive potentials.⁵ This biological condition is responsible for the formation of populations with vertiginous expansive growth in underground networks in the microhabitats of the hidden environment of urban areas in Brazilian cities.²¹ Considering the population dynamics of this species, at theoretical reproduction rates, 2 parthenogenetic females of T serrulatus could yield 33 million specimens in the fifth generation.²² Measuring the real size of this underground population in rainwater galleries and sewage networks in the municipality of Americana would be a challenge, without reliable responses.

In this municipality, mechanical control activities and health surveillance services were carried out, with nighttime capture of scorpions using ultraviolet light.²³ This resulted in a collection of 119,675 specimens over the period analyzed (1998–2018). Nonetheless, the epidemiological rates of scorpionism remained very high, with coefficients of >150 accidents per 100,000 inhabitants over the last 4 y. Nevertheless, the Brazilian Ministry of Health still does not recommend the use of chemical control of scorpions.²⁴

Limitations

The information registered on SINAN that was obtained may have contained some biased data. This conceivably could have affected our analysis of the geographical locations of reported scorpion stings.

Some chronologically based sampling biases may have been introduced because the information on the variables of geographical characterization of the UPAs was limited to a descriptive analysis performed in the year 2018. The analysis was, thus, focused because of incongruences in the municipal institution’s database for previous years during the period of analysis.

Conclusions

This analysis demonstrated an increased risk of scorpion envenomation in different Americana UPAs. The incidence and hotspots maps improved the understanding of the spatial distribution of scorpionism as a public health problem in the municipality, aiming toward better prevention of scorpion stings and control of urban infestation of scorpions in areas at a greater risk.

Footnotes

Acknowledgments

The authors thank the collaborators of the Tick and Scorpion Surveillance and Control Program of the Health Secretariat of Americana, São Paulo state for their active participation in the field work. The authors also thank to Dr Claudio Mauricio Vieira de Souza for collaboration in the critical revision of English language.

Author Contributions: study concept and design (JBN); data acquisition (JBN, VDD); data analysis (JBN, VDD, FSF); drafting and critical revision of the final manuscript (JBN, VDD, FSF).

Financial/Material Support: None.

Disclosures: None.

References

Bochner

Souza

C.M.

Divergences between the Brazilian national information systems for recording deaths from venomous animals. J Venom Anim Toxins Incl Trop Dis 2019; 25 e143018 http://dx.doi.org/10.1590/1678-9199-JVATITD-1430-18.

Chippaux

J.P.

Goyffon

Epidemiology of scorpionism: a global appraisal. Acta Trop 2008; 107(2), 71–79.

Chippaux

J.P.

Emerging options for the management of scorpion stings. Drug Des Devel Ther 2012; 6, 165–173 http://dx.doi.org/10.2147/DDDT.S24754.

Santos

M.S.

Silva

C.G.

Neto

B.S.

Júnior

C.R.

Lopes

V.H.

Júnior

A.G.

et al. Clinical and epidemiological aspects of scorpionism in the world: a systematic review. Wilderness Environ Med 2016; 27(4), 504–518.

Lourenço

W.R.

The evolution and distribution of noxious species of scorpions (Arachnida: Scorpiones). J Venom Anim Toxins Incl Trop Dis 2018; 24, 1 https://doi.org/10.1186/s40409-017-0138-3.

Lourenço

W.R.

What do we know about some of the most conspicuous scorpion species of the genus Tityus? A historical approach. J Venom Anim Toxins Incl Trop Dis 2015; 21, 1–12 20 https://jvat.biomedcentral.com/articles/10.1186/s40409-015-0016-9.

Von Eickstedt

V.R.

Ribeiro

L.A.

Candido

D.M.

Albuquerque

M.J.

Jorge

M.T.

Evolution of scorpionism by Tityus bahiensis (Perty) and Tityus serrulatus Lutz and Mello and geographical distribution of the two species in the state of São Paulo-Brazil. J Venom Anim Toxins Incl Trop Dis 1996; 2(2), 92–105.

Brites-Neto

Duarte

K.M.

Modeling of spatial distribution for scorpions of medical importance in the São Paulo state, Brazil. Vet World 2015; 8(7), 823–830.

Lourenço

W.R.

Scorpion incidents, misidentification cases and possible implications for the final interpretation of results. J Venom Anim Toxins Incl Trop Dis 2016; 22, 21 https://doi.org/10.1186/s40409-016-0075-6.

10.

Lourenço

W.R.

Scorpions and life-history strategies: from evolutionary dynamics toward the scorpionism problem. J Venom Anim Toxins Incl Trop Dis 2018; 24, 19 https://doi.org/10.1186/s40409-018-0160-0.

11.

Pimenta

R.J.

Brandão-Dias

P.F.

Leal

H.G.

Carmo

A.O.

Oliveira-Mendes

B.B.

Chávez-Olórtegui

et al. Selected to survive and kill: Tityus serrulatus, the Brazilian yellow scorpion. PLoS One 2019; 14(4)e0214075.

12.

Brites-Neto

Brasil

Scorpion control strategies in the city of Americana, SP. Bol Epidemiol Paul 2012; 9(101), 4–15.

13.

Feliciano MA. Informativo socioeconômico do município de Americana, São Paulo, Brasil. Americana, Brazil: SEPLAN; 2019. Available at: http://www.americana.sp.gov.br/download/planejamento/D032_Informativo_SocioEconomico_2019.pdf. Accessed on May 25, 2022..

14.

Kanankege

K.S.

Alvarez

Zhang

Perez

A.M.

An introductory framework for choosing spatiotemporal analytical tools in population-level eco-epidemiological research. Front Vet Sci 2020; 7, 339 Available at: http://www.americana.sp.gov.br/download/planejamento/D032_Informativo_SocioEconomico_2019.pdf. Accessed on May 25, 2022.

15.

Chaiblich

J.V.

Lima

M.L.

Oliveira

R.F.

Monken

Penna

M.L.

Spatial study of risks to leptospirosis in the municipality of Rio de Janeiro (RJ). Saúde Debate 2017; 41(SPE2), 225–240 Available at: http://www.americana.sp.gov.br/download/planejamento/D032_Informativo_SocioEconomico_2019.pdf. Accessed on May 25, 2022.

16.

Carvalho

Magalhães

M.A.

Medronho

R.D.

Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012. Rev Saúde Pública. 2017; 51, 79 Available at: http://www.americana.sp.gov.br/download/planejamento/D032_Informativo_SocioEconomico_2019.pdf. Accessed on May 25, 2022.

17.

da Saúde

Ministério

Acidentes escorpiônicos no Brasil, 2018. Secretaria de vigilância em saúde. Bol Epidemiológico. 2019; 50(28), 17–21.

18.

Eloy

Camargo

Spinola

Paulo

Malaque

Gallafrio

et al. Scorpionism in the state of São Paulo: operational restructuring for timely service to victims [in Spanish]. Bol Epidemiol Paul 2021; 18(209), 16–30.

19.

Azevedo

T.S.

Lorenz

Chiaravalloti-Neto

Scorpionism in the state of São Paulo: the application of a potential distribution model in the mapping of outbreak risk areas in present and future scenarios. In: Ribeiro

E.A.

Miranda

Castro

R.C.

eds. Environmental Changes, Disasters and Social Vulnerability. Blumenau, Brazil , Federal Institute of Santa Catarina, 2019, 36–43.

20.

El Hidan

M.A.

Kahime

Laaradia

M.A.

Bouimeja

Aabadi

Mansour

A.A.

et al. Climate change, scorpion ecology, and envenomation: what are the links?. In: Kahime

El Hidan

M.A.

El Hiba

Sereno

Bounoua

eds. Handbook of Research on Global Environmental Changes and Human Health , Hershey, PA: Engineering Science Reference, 2019, 460–474.

21.

Souza

C.M.

Notes on scorpionism in Brazil and the effort to control it. Vetores Pragas 2012; 30, 19–23.

22.

Lourenço

W.R.

Cloudsley-Thompson

J.L.

Cuellar

Eickstedt

V.V.

Barraviera

Knox

M.B.

The evolution of scorpionism in Brazil in recent years. J Venom Anim Toxins 1996; 2(2), 121–134.

23.

Brites-Neto

Galassi

G.G.

Monitoramento Epidemiological monitoring of Tityus serrulatus in urban areas using an ultraviolet light device. Vetores Pragas 2012; 30, 16–18.

24.

da Saúde

Ministério

. Manual de controle de escorpiões. Brasil. Departamento de vigilância epidemiológica. Brasília. Secretaria de Vigilância em Saúde, 2009: Available at: https://bvsms.saude.gov.br/bvs/publicacoes/manual_controle_escorpioes.pdf. Accessed on May 10, 2022.