Spatial Analysis of Mosquitoes Collected From Urban Automotive-related Shops and Junkyards in South Mexico.

doi:10.21203/rs.3.rs-4619051/v1

Download PDF

Research Article

Spatial Analysis of Mosquitoes Collected From Urban Automotive-related Shops and Junkyards in South Mexico.

https://doi.org/10.21203/rs.3.rs-4619051/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Automotive-related shops have been recognized as significant locations for the production of mosquitoes. The potential risk posed by non-residential premises as relevant early transmission sites is sometimes neglected. In Mexico, exist more than 244 142 automotive-related shops; which are generally not regulated by any health authority. In this study, we collected and identified larvae and adults from urban automotive-related premises in the city of Villahermosa in Tabasco, southern Mexico. The analysis of the collected species and each type of non-residential premise was conducted using a Generalized Linear Model. For special analyses of collected individuals, the average nearest neighbor, general G function, Moran's Index, semi-variogram, and kriging analysis were used. A total of 676 non-residential premises were examined. The most common establishments were automobile workshops, auto body, and paint shops. Aedes aegypti was an abundant specie, followed by Ae. albopictus, and Cx. coronator. Culex interrogator, Cx. nigripalpus, Ae. taeniorhynchusand An. Albimanus were also observed. Junkyards, cemeteries, and tire repair shops exhibited a relative higher level of productivity for mosquitoes.Ae. aegypti and Ae. albopictus were highly clustered in the northeast part of the city. While Culex spp were more concentrated in the center-south of the city. The northern region comprises both industrial and residential properties. Our findings indicated that programs of Ae. aegypti surveillance and control should consider the epidemiological significance of automotive-related and other non-residential premises.

spatial analyses

non-residential premises

urban mosquitoes

vector control.

In Mexico, dengue fever and, to a lesser extent, Zika and chikungunya are the main mosquito-borne viral diseases (MBDs). However, the health services of the country are constantly on the lookout for risk factors for emergence of other MBDs (e.g. West Nile fever, equine encephalitis, etc.). Continuous outbreaks of MBDs, particularly in cities and surrounding areas, are a major public health concern (see DGE 2010–2023). Aedes aegypti is the main vector of MBDs in Mexico. Meanwhile, the occurrence of Ae. albopictus in endemic dengue areas has also been reported in several states (see Ortega et al. 2022) and an impact as a relevant vector is highly possible. Aedes mosquitoes prefer to feed on human blood and use human-made containers for larval development; therefore, residential household areas have been under constantly surveyed and monitored for these species.

Non-residential commercial premises such as schools, cemeteries, tire repair shops, construction sites, junkyards, are also important sources of breeding sites, and a risk for MBDs transmission in that job-site environments (Wilke et al. 2019; Perez-Perez et al. 2021). Previous studies have shown that these types of premises tended to accumulate large quantities of potential breeding sites for Ae. aegypti and may be infested with adult mosquitoes (see: Morrison et al. 2006; dos Reis et al. 2010; Zarate-Nahon et al. 2013). Therefore, urban residents working in or visiting that premises could be bitten by infected mosquitoes at any time, becoming potential hosts carriers for pathogens in their household area.

Mexican cities are a heterogeneous mosaic of residential, non-residential, mixed-used, public-use zones, wetlands, streams, natural/artificial lakes and ponds. Most of them have climatic conditions suitable for harboring large populations of vector mosquitoes, and major epidemics have been recorded in these urban areas. However, within cities, there are areas where a large fraction of MBDs cases is concentrated (hotspots). The identification of hotspots has been helpful for canalizing prevention and control activities, especially in residential areas. Nevertheless, the potential risk posed by non-residential premises as relevant early transmission sites is sometimes neglected (especially those outside a hotspot) (see Dos Reis et al. 2010), and prevention and control measures cannot be fully implemented. Automotive-related shops have been recognized as important places for mosquito production (Chiaravalloti-Neto 1997). These types of facilities are prevalent sources of containers, particularly of discarded tires. This is due to the fact that certain facilities tended to neglect fundamental sanitation measures and proper disposal of solid and liquid waste.

In Mexico, exist more than 244 142 automotive-related shops. Automotive-related shops have come under constant scrutiny as they are hazardous waste generating sites (see García-Sanchez et al. 2023). Generally, they are not supervised by any regulatory health authority. For these reasons, vehicle repair premises, autobody and paint shops, junkyards, and tire repair shops were selected for larvae an adult collection.

In this study, we collected and identified larvae and adults from urban automotive-related premises in the city of Villahermosa, Tabasco in southern Mexico. Villahermosa City is the capital and the most populous municipality of the state, with a high prevalence of dengue fever. Despite Villahermosa City significant landscape modifications and loss of forest cover, species belonging to the Aedeomyia, Aedes, Anopheles, Coquilletidia, Culex, Mansonia and Uranotaenia genera have been reported in home environments (Torres-Chable et al. 2017). The goal of our research is to provide information that accounts for the heterogeneity and diversity of species in non-residential premises in the city. Also, we studied the spatial patterns of detected mosquito species. The identification of neglected premises (not usually targets for vector surveillance and control) with a number of breeding sites, could be useful for expanding surveillance and vector control measures in non-residential areas.

Study site

The study was conducted from February to June 2022 (dry season) in the city of Villahermosa (17°59′16″N, 92°55′09″W; Fig. 1), the capital of the state of Tabasco. It covers an area of 61 km² with 340,060 inhabitants (INEGI 2020). The city is at 10 meters above sea level and is located within the hydrological region of the Grijalva-Usumacinta River basin. A tropical monsoon (AM) and a trade-wind littoral climate dominate the area. The mean annual temperature is 27°C and the rainfall is 1,144 mm in dry season and 3,091 mm in the rainy season (INEGI 2017).

Non-residential premises selected for mosquitoes’ collections

In Villahermosa, this type of premises operates without adequate water infrastructure and waste management. Generally, they are not supervised by any regulatory health authority. For these reasons, these types of facilities vehicle repair premises, autobody and paint shops, junkyards, and tire repair shops were selected for larvae an adult collection. Cemeteries near the facilities were also collected (Fig. 2).

Collections

Transfer pipettes were used for larval collection. Collected larvae were placed in bottles containing 96% alcohol. For adult collection a battery-powered bazooka-like aspirators were used (Fig. 3). Collected adults were placed in paper cups covered with netting, Georeferenced coordinates for each collection site were obtained using a handheld GPS. The collected organisms were then transported to the laboratory where they were counted and identified under stereo-microscope with 50x magnification. Taxonomic identification was based on morphological identification keys (Ibañez-Bernal and Martínez-Campo 1994). The collected material was deposited at the Bioassays and Entomological Research Unit (Unidad de Bioensayos e Investigación Entomológica) in Villahermosa, Tabasco, México.

Statistical analysis

A Generalized Linear Model (GLM), assuming a Poisson distribution and log link function, using number of organisms collected as dependent variable; specie and each type of non-residential Premises and their interaction were included factorially as explanatory variables was performed. Statistical analyses were done in Statistica 10 (Statsoft Inc. 1984–2011).

Spatial analyses

Spatial distribution pattern was conducted by pattern analysis using ArcGis Pro (ESRI, Redlands, CA, USA) average nearest neighbor (ANN) analysis to determine whether the spatial distribution of mosquito species was due in part to chance or non-random spatial clustering. To identify spatial clusters of highest incidence rates (hotspots) and low values (coldspots) of each species, within the context of neighboring features, we used the General G function (Getis-Ord) in the mapping cluster option in ArcGis Pro.

The Moran's Index analysis (using ArcGis Pro) was employed to evaluate the degree of spatial autocorrelation or independence in the number of mosquito species collected. The analysis determined whether mosquito collecting points were randomly distributed or whether there was significant clustering of collecting points. The weight distance matrix was based on Euclidean distance.

The degree of spatial variability for data of each specie was determined by using semi-variogram and kriging analysis. The best theoretical model (spherical, exponential, or Gaussian) and its parameters (nugget, partial sill, and range) were determined by analyzing the variogram. In order to verify the reliability of the fitted models, and to contrast the estimated values from the variogram models with the actual values, cross-validation error measurements were used. We utilized the Kriging spatial interpolation technique to generate a prediction surface based on measured values and the distance to the predicted locations. Ordinary Kriging was chosen as the preferred model because the unknown mean is estimated for each location based on nearby data. Analyses were conducted using ArcGis Pro.

Statistical analysis

676 non-residential premises were surveyed for the presence of larvae and adult mosquitoes. The most common establishment were the automobile workshops (N = 457) followed by tire repair shops (N = 73), auto body and paintshops (N = 99), junkyards (N = 38), and cemeteries (N = 9). Differences in the number of collected organisms per establishment were detected (GLM, χ² = 194.14, P < 0.001)

A total of 20,595 organisms were collected. Six species were collected; we detected differences in the number of collected organisms per specie (GLM, χ² = 871.32, P < 0.001). Aedes aegypti was an abundant specie (larvae and adults, N = 8,062), followed by Ae. albopictus (larvae and adults, N = 2,396), Cx. coronator (larvae, N = 688), Cx. interrogator (larvae, N = 24), Cx. nigripalpus (larvae, N = 28), and Cx. quinquefasciatus (larvae, N = 464). Adults of Culex spp. were also collected (N = 8,332); however, the loss or damage of pertinent taxonomic characteristics impeded the accurate identification of all the species. Therefore, we decided to conduct analyses and identify this group as “Culex spp. Adults”. Additionally, two larvae of Ae. taeniorhynchus were collected in an auto body and paint shop, four larvae of An. albimanus were collected in a cemetery, and one larva of Ur. lowii was collected in an automobile workshop. Nevertheless, these three species were not considered for further analysis.

We also detected differences in the Premises*Specie interaction (GLM, χ² = 468.16, P < 0.001). Due to the large presence of automobile workshops and the number of organisms collected at these sites, these premises could be considered the most productive. Nonetheless, when weighing the quantity of organisms collected against the number of premises where they were collected, other premises showed a greater risk. For instance, it can be observed that junkyards, cemeteries, and tire repair shops exhibited a relative higher level of productivity for Ae. aegypti compared to automobile workshops (Table 1). Meanwhile, Ae. albopictus and Culex spp. Adults had a relative higher presence in cemeteries and automobile workshops. Larvae of Cx. coronator presence was relative higher in cemeteries. Meanwhile, for Cx. interrogator and Cx. nigripalpus automobile workshops were productive. For Cx. quinquefasciatus, auto body and paintshops showed relative higher productivity.

Table 1

Number of mosquitoes of species collected in automotive -related premises in Villahermosa, Tabasco
		Ae. aegypti	Ae. albopictus	Culex spp. adults	Cx. coronator	Cx. interrogator	Cx. nigripalpus	Cx. quinquefasciatus
Auto body and paintshop	# Premises	84	25	76	11	--	1	4
	# Organisms	1180	298	1005	77	--	4	53
	Relativization	14.05	11.92	13.22	7	--	4	13.25
Automobile workshop	# Premises	349	102	381	59	3	8	37
	# Organisms	5062	1623	5946	455	20	18	325
	Relativization	14.5	15.91	15.61	7.71	6.67	2.25	8.78
Cemetery	# Premises	6	4	6	3	--	2	3
	# Organisms	153	97	92	49	--	3	15
	Relativization	25.5	24.25	15.33	16.33	--	1.50	5
Junkyard	# Premises	31	13	29	8	1	1	5
	# Organisms	903	219	337	57	4	3	30
	Relativization	29.13	16.85	11.62	7.13	4	3	6
Tire repair shop	# Premises	61	14	64	9	--	--	7
	# Organisms	1358	159	952	50	--	--	41
	Relativization	22.26	11.36	14.88	5.56	--	--	5.86
Relativization= #Organisms/#Premises

Spatial analyses

Five species showed significant calculated value for the ANN index. For Ae. aegypti, ANN was found to be 132.64 m, whereas the calculated expected mean distance was 266.06 m. and was statistically clustered with an R value of 0.49 (Z = -22.1, P < 0.001). Aedes albopictus showed an ANN of 299.25 m, the calculated expected mean distance was 474.43 m, R value of 0.63 (Z= -8.88, P < 0.001). The ANN for Cx. coronator was 400.89, with an expected mean distance of 643.38 and an R value of 0.62 (Z = -68.4, P < 0.001). The ANN index for Culex spp. Adults was 140.81, the calculated expected mean was 268.24, and an R = 0.52 (Z = -21.43, P < 0.001). Finally, Cx. quinquefasciatus showed an ANN of 535.76, expected mean distance of 663.57 with and R of 0.80 (Z = -2.75, P = 0.006).

Related, areas with various risk levels of Ae. aegypti, Ae. albopictus, Cx. coronator, Culex spp Adults and Cx. quinquefasciatus were identified with a significance greater than or equal to 90% using the Getis-Ord Gi٭ (Fig. 4). Clusters of Ae. aegypti and Ae. albopictus were identified in the northeastern region of the city. For Cx. coronator and Cx. quinquefasciatus, small and low clusters were detected at the southwest region of the city. The other species did not exhibit significant clustering.

The spatial autocorrelation analysis with Moran’s I Index showed the highly significant positive clustering of similar values in close geographical range of the spatial distribution of Ae. aegypti and Culex spp. Adults (Table 2). For the remaining species, the spatial analysis using Moran's I found no evidence of spatial structure (P > 0.5 in all cases). For Ae. aegypti, the highest Morean I was detected after a distance of 15 m, indicating that the spatial dependence in the abundance is the most significant at the separation distance of 15 meters. For Culex spp adults, the highest Moran's I value was observed at 55 meters.

Table 2

Moran's I spatial autocorrelation index for all the mosquito species collected in automotive -related premises in Villahermosa, Tabasco
Specie	Moran's I	z-score	P
Ae. aegypti	0.529	8.1945	0.015
Ae. albopictus	0.0682	0.863	0.38
Culex spp. adults	0.385	4.1855	< 0.001
Cx. coronator larvae	-0.0468	-0.628	0.529
Cx. interrogator larvae	-0.9565	-0.9572	0.338
Cx. nigripalpus larvae	-0.3854	-1.1005	0.27
Cx. quinquefasciatus larvae	-0.0026	0.1749	0.86

Data from species with significant spatial autocorrelation were analyzed using kriging analysis (i.e. Ae. aegypti and Culex spp Adults). Nevertheless, due to its significance as an active arbovirus vector, the analysis was also conducted for Ae. albopictus. Table 2 provides an overview of the model’s parameters for each species semi-variogram. The Spherical, Gaussian, and Exponential models exhibited similar Kriging interpolation parameters. The Gaussian model showed the highest nugget values for the three species, suggesting that the observed spatial variability could be driven by small-scale artifacts or distant collecting points that are likely to carry significant weight.

The absence of a nugget effect for Ae. albopictus within the Spherical and Exponential models suggests that its spatial dissemination occurs at broader geographic scales (Table 2). Aedes albopictus has the highest partial sill value, indicating the greatest overall variability among the three species. In contrast, Ae. aegypti exhibits lesser levels of variability in their spatial patterns in comparison to Ae. albopictus and Culex spp Adults. Culex spp. Adults has the largest overall effective range among the three species, which indicates that its spatial influence exceeds that of Aedes species.

Table 3

Comparison of the Spherical, Exponential and Gaussian semi-variogram models for *Ae. aegypti*, *Ae. albopictus* and *Culex* spp. Adults. ME = Mean Error, RMSE = Root Mean Square Error, MSE = Mean Standardized Error, RMSSE = Root Mean Square Standardized Error, ASE = Average Standard Error
	Spherical	Gaussian	Exponential
	Ae. aegypti
Nugget	237.35	245.23	244.03
Range	0.0008	0.0008	0.0008
Partial Sill	84.03	83.90	81.46
ME	-0.25	-0.23	-0.26
RMSE	17.77	17.76	17.77
MSE	-0.01	-0.01	-0.01
RMSSE	0.94	0.94	0.94
ASE	18.85	19.00	18.95
	Ae. albopictus
Nugget	0	103.97	0
Range	0.00081	0.00081	0.00107
Partial Sill	526.95	469.49	556.00
ME	0.08	0.05	0.13
RMSE	20.99	21.26	21.14
MSE	0.01	0.01	0.01
RMSSE	0.89	0.88	0.87
ASE	23.69	24.50	24.30
	Culex spp. Adults
Nugget	411.49	471.84	328.18
Range	0.004	0.004	0.004
Partial Sill	261.24	207.78	350.13
ME	0.02	0.02	0.04
RMSE	23.31	23.28	23.49
MSE	0.00	0.00	0.00
RMSSE	0.95	0.94	0.96
ASE	25.06	25.16	25.00

Related, the Spherical, Gaussian, and Exponential models all showed similar cross-validation parameters (Table 2). For Ae. aegypti and Culex spp. Adults, the Gaussian MSE and RMSE values were slightly lower than the values of the two other models. Meanwhile, the Spherical model for Ae. albopictus exhibited the lowest RMSE value; however, the ME value was higher for the Gaussian model. According to the Spherical model, the ASE is somewhat closer to the RMSE for the three species. For Ae. albopictus, the RMSSE was closer to 1 under the Spherical model, however, for Culex spp. Adults was higher under the Gaussian model. For Ae. aegypti, the RMSSE was similar across all models. For Ae. aegypti and Culex spp. Adults, predicted maps were generated using the Gaussian model, whereas for Ae. albopictus, the Spherical model was used (Fig. 5). The maps revealed an important risk of Ae. aegypti, Ae. albopictus, and Culex spp. Adults in the northern zone of the city. For Culex spp. Adults, the risk is along the city, followed by Ae. aegypti, for Ae. albopictus, the risk is lower.

The almost 700 premises surveyed demonstrated their potential risk as breeding sites for vector species. As expected, Ae. aegypti, and Cx. quinquefasciatus demonstrated the capacity of the species to exploit urbanized habitats. It is noteworthy that Cx. coronator, a potential vector of West Nile and Zika virus, was observed in all the types of premises surveyed, indicating that it is a generalist species in terms of breeding-site preferences. Aedes albopictus has been steadily increasing its presence in the country (see Ortega-Morales et al. 2022), its presence in Villahermosa is indicative of the favorable environmental conditions of the city for its establishment.

Cemeteries were the most productive environments for Ae. aegypti, Ae. albopictus and some Culex species. Our results continue to demonstrate the importance of cemeteries as vector sources in urban areas (see also Abe 2005; Otero et al. 2022; Wilke et al. 2020). Certain premises were breeding sites for species identified as potential but not relevant vectors in urban habitats of Mexico (i.e. Cx. coronator, Cx. interrogator, Cx. nigripalpus, Ae. taeniorhynchus and An. albimanus). It is probable that the species areadapting to man-made environments. Aedes taeniorhynchus and An. albimanus commonly lay eggs in large water bodies (e.g. lakes, streams, ponds) (see Rodriguez-Martinez et al 2023), their low presence in our collections could be attributed to the proximity of water bodies to the premises surveyed.

The spatial analyses showed that Ae. aegypti, Ae. albopictus were highly clustered in the northeast part of the city and, Culex spp. Adults. While Culex were more concentrated in the center-south of the city, and to a lesser extent in the northeast region. These hotspots should be considered monitoring points for the density of vector mosquito species. Interestingly, the center of the city showed cold spots for Ae. aeygpti and Culex spp. Adults, indicating that the area is not suitable for harboring large numbers of organisms of these species. It could be argued that routine application of insecticide and cleaning activities are exerting a significant impact on this particular sector of the city. However, some hotspots for Cx. coronator and Cx. quinquefasciatus were detected. Both species have shown their ability to exploit the resources present in urban areas and establish themselves in areas with substantial anthropogenic land use and land cover transformations (Conelly et al. 2016; Wilke et al. 2021). It is noteworthy that in previous surveys conducted in the water bodies of Villahermosa, the presence of these two species was low, indicating their possible adaptation to artificial breeding sites such as those surveyed in this study (see Rodriguez-Martinez et al. 2023). This prior observation, and our findings, indicate that both species possess the capability to utilize resources available in non-residential urban premises on a microgeographic scale. The potential risk posed by these two species as vectors should not be neglected.

Spatial analyses and predictive models supported importance of the northeast area of the city. Within this area of the city is located the Ciudad Industrial Complex (Fig. 6.). It currently has an area of 141.81 hectares, with most of its facilities dedicated to the processing of agricultural products, food processing, and support services for restaurants, hotels, and warehouses (DOF 2000). Ciudad Industrial is surrounded by several residential complexes (Fig. 6.) exhibiting the highest proportion of dwellings lacking sewerage and a significant number of vulnerable areas to flooding in the city (DOF 2000; Vazquez-Cendon et al. 2016).

The Ciudad Industrial and residential areas did not exhibit the highest number of collecting sites (Fig. 1). However, the presence and number of Ae. aegypti individuals indicated that the area was suitable for the occurrence of the species. It can be inferred that the industrial and residential premises may possess numerous potential breeding grounds. Although the residential area could be continuously under chemical and integrated control strategies, the industrial premises may act as a sourcing area. No clear prediction for Ae. albopictus was detected. Despite the specie has been found in 75% of the states of Mexico, its presence is still not as wide and abundant as Ae. aegypti. However, its presence in highly urbanized areas has become increasingly frequent, and collected organisms have been found to be infected with different arboviruses (Correa-Morales unpublished data). It is anticipated that its contribution as a primary vector of arbovirus in Mexico will soon be compared to that of Ae. aegypti. It is possible that the absence of risk of Ae. albopictus may be due to the low density of the specie in Villahermosa. Nevertheless, the species exhibit a significant degree of adaptability to man-made containers due to the decline of forest areas surrounding the city. Its presence in residential and non-residential premises must be continuously analyzed.

Our findings showed that programs of Ae. aegypti surveillance and control must take into account the epidemiological significance of non-residential premises. The analyses conducted in this study indicate that the production of Ae. aegypti (and Ae. albopictus) in non-residential sites holds significance. However, it is also important that the priorities of vector-control programs should remain focused on residential sites, although additional research on the role of non-residential sites, especially those neglected into the surveillance and control programs, is needed.

Acknowledgments We thank Arturo Pérez-de la Cruz, Magdalena Hernández-Jiménez and José Antonio Torres-Ortiz for their assistance with fieldwork.

Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability All data generated or analyzed during this study are included in this article.

Conflict of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abe M, McCall, P J, Lenhart, A, Villegas, E, Kroeger, A (2005) The Buen Pastor cemetery in Trujillo, Venezuela: measuring dengue vector output from a public area. TM & IH 10: 597–603. https://doi.org/10.1111/j.1365-3156.2005.01428.x
Chiaravalloti Neto F (1997) Description of the colonization of Aedes aegypti in the region of São José do Rio Preto, São Paulo (in Portuguese). Rev Soc Bras Med Trop 30: 279–285. https://doi.org/0.1590/s0037-86821997000400002
DOF-Diario Oficial de la Federación (2023) Urban development program of Tabasco, Centro (In spanish) (PMDU CENTRO-Periódico Oficial). https://tabasco.gob.mx/programa-municipal-de-desarrollo-urbano-de-centro. Accessed 02 march 2024
Dos Reis IC, Honório NA, Codeço CT, Magalhães MdeA, Lourenço-de-Oliveira R, Barcellos C (2010) Relevance of differentiating between residential and non-residential premises for surveillance and control of Aedes aegypti in Rio de Janeiro, Brazil. Acta Trop 114(1): 37–43. https://doi.org/10.1016/j.actatropica.2010.01.001
García-Sánchez S, Juárez-Agis A, Maldonado-Astudillo RI, Olivier-Salome B, Zeferino-Torres J, Torres-Espino G, Rivas-González M (2023) Situación actual y cumplimiento de la normatividad sobre residuos peligrosos en talleres mecánicos en la Colonia Progreso, Acapulco, Guerrero, México. Acta Univ 33: 1–12. https://doi.org/10.15174/au.2023.3747
Ibañez-Bernal S, Martínez-Campos C (1994) Identification key of common mosquito larvae in urban and suburban areas of the Mexican Republic (Diptera: Culicidae) (In Spanish). Folia Entomol Mex 92: 43–73
INEGI (2017) Anuario estadístico y geográfico de Tabasco 2017. Instituto Nacional de Estadística y Geografía. https://www.inegi.org.mx/contenidos/productos/prod_serv/contenidos/espanol/bvinegi/productos/nueva_estruc/anuarios_2017/702825095123.pdf. Accessed 13 April 2024
INEGI (2020) Cuestionario Básico del Censo 2020, Tabasco. Instituto Nacional de Estadística y Geografía. https://www.inegi.org.mx/contenidos/saladeprensa/boletines/2021/EstSociodemo/ResultCenso2020_Tab.docx. Accessed 13 April 2024
Morrison AC, Sihuincha M, Stancil JD, Zamora E, Astete H, Olson JG, Vidal-Ore C, Scott TW (2006) Aedes aegypti (Diptera: Culicidae) production from non-residential sites in the Amazonian city of Iquitos, Peru. Ann Trop Med Parasitol 100: Suppl 1, S73–S86. https://doi.org/10.1179/136485906X105534
Ortega-Morales AI, Pérez-Rentería C, Ordóñez-Álvarez J, Salazar JA, Dzul-Manzanilla F, Correa-Morales F, Huerta-Jiménez H (2022) Update on the dispersal of Aedes albopictus in Mexico: 1988–2021. Front Trop Dis 2: 72. https://doi.org/10.3389/fitd.2021.814205
Otero LM, Medina-Martinez G, Sepúlveda M, Acevedo V, Toro M, Barrera R (2022) Cemeteries as sources of Aedes aegypti and other mosquito species in southeastern Puerto Rico. TM & IH 27(3): 300–309. https://doi.org/10.1111/tmi.13723
Pérez-Pérez J, Peña-García VH, Calle-Tobón A, Quimbayo-Forero M, Rojo R, Henao E, Shragai T, Rúa-Uribe G (2021) Entomovirological surveillance in schools: are they a source for arboviral diseases transmission? Int J Environ Res Public Health 18(11):6137. https://doi.org/10.3390/ijerph18116137
Rodríguez-Mártínez LM, Correa-Morales F, González-Acosta C, Moreno-García M (2023) Study of mosquito (Culicidae) larvae and characterization of water bodies in urban and periurban areas. Can Entomol 155: e23. https://doi.org/doi:104039/tce20239
Torres-Chable OM, Baak-Baak CM, Cigarroa-Toledo N, Zaragoza-Vera CV, Arjona-Jimenez G, Moreno-Perez LG, Garcia-Rejon JE (2017) Mosquito fauna in home environments of Tabasco, Mexico. Southwest Entomol 42(4): 969–982. https://doi.org/10.3958/059.042.0416
Vázquez-Cendón ME, González-Aguirre JC, Alavez-Ramírez J (2016) Numerical simulation of flooding in Villahermosa Mexico using IBER code (in Spanish). Ing Agua 20(4): 201–216. https://doi.org/10.4995/ia.2016.5231
Wilke ABB, Caban-Martinez AJ, Ajelli M, Vasquez C, Petrie W, Beier JC (2019) Mosquito adaptation to the extreme habitats of urban construction sites. Trends Parasitol 35(8):607–614. https://doi.org/10.1016/j.pt.2019.05.009
Wilke ABB, Vasquez C, Carvajal A, Moreno M, Diaz Y, Belledent T, Gibson L, Petrie WD, Fuller DO, Beier JC (2020) Cemeteries in Miami-Dade County, Florida are important areas to be targeted in mosquito management and control efforts. PloS One 15(3): e0230748. https://doi.org/10.1371/journal.pone.0230748
Zarate-Nahon EA, Ramirez-Jimenez R, Alvarado-Moreno MS, Sanchez-Casas RM, Laguna-Aguilar M, Sanchez-Rodriguez OS, et al (2013) Aedes aegypti mosquitoes at nonresidential sites might be related to transmission of dengue virus in Monterrey, Northeastern Mexico. Southwest Entomol 38: 465–76. https://doi.org/10.3958/059.038.0309

Download PDF

Reviewers agreed at journal
15 Jul, 2024
Reviewers invited by journal
15 Jul, 2024
Editor assigned by journal
24 Jun, 2024
First submitted to journal
21 Jun, 2024

You are reading this latest preprint version

Spatial Analysis of Mosquitoes Collected From Urban Automotive-related Shops and Junkyards in South Mexico.

Status:

Version 1

Abstract

Figures

Introduction

Materials

Study site

Non-residential premises selected for mosquitoes’ collections

Collections

Statistical analysis

Spatial analyses

Results

Statistical analysis

Spatial analyses

Discussion

Declarations

References

Status:

Version 1