Spatial analysis of the natural infection index for Triatomines and the risk of Chagas disease transmission in Northeastern Brazil

ABSTRACT

This study aimed to analyze the spatial pattern of natural infection index (NII) for triatomines and the risk of Chagas disease transmission in an endemic area of Northeastern Brazil. An ecological study was conducted, based on 184 municipalities in five mesoregions. The NII for triatomines was evaluated in the Pernambuco State, Brazil, from 2016 to 2018. Spatial autocorrelations were evaluated using Global Moran Index (I) and Local Moran Index (II) and were considered positive when I > 0 and p < 0.05, respectively. In total, 7,302 triatomines belonging to seven different species were detected. Triatoma brasiliensis had the highest frequency (53%; n = 3,844), followed by Triatoma pseudomaculata (25%; n = 1,828) and Panstrongylus lutzi (18.5%; n=1,366). The overall NII was 12%, and the higher NII values were P. lutzi (21%) and Panstrongylus megistus (18%). In the mesoregions of Zona da Mata, Agreste, Sertao, and Sertao do Sao Francisco, 93% of triatomines were detected indoors. The global spatial autocorrelation of I to NII was positive (0.2; p = 0.01), and II values calculated using BoxMap, MoranMap, Lisa Cluster Map were statistically significant for natural infections. With regard to the risk areas for the presence of triatomines, Zone 2 (the Agreste and Sertao regions) presented a relative risk of 3.65 compared to other areas in the state. Our study shows the potential areas of vector transmission of Chagas disease. In this study, the application of different methods of spatial analysis made it possible to locate these areas, which would not have been identified by only applying epidemiological indicators.

Chagas disease; Epidemiology; Triatomine; Spatial analysis

INTRODUCTION

The species of triatomines responsible for the transmission of Chagas disease has a wide distribution and can easily adapt to household environments. The colonization of triatomines occurs due to constant changes in the natural environment caused by anthropic activities that have led to an imbalance in the ecosystem and a modification of vector behavior¹-³.

From the South of the United States, where 11 species have been found⁴, to the South of Argentina and Chile, where 156 triatomine species (153 living and three fossils) that are responsible for the transmission of Chagas disease have been found⁵-⁸. Eight species of the Triatoma genus, especially Triatoma rubrofasciata, have been found in Africa, the Middle East, Southeast Asia, and the Western Pacific⁵,⁹. In Latin America, triatomines represent a substantial public health problem, as these insects transmit Trypanosoma cruzi (Chagas, 1909) in Bolivia, Argentina, Mexico, Brazil, Chile, Ecuador, Peru, Paraguay, Uruguay, Venezuela, Colombia, the Guianas, and throughout Central America¹,¹⁰-¹².

In 2006, Brazil received an international certification for eradicating the transmission of the disease caused by Triatoma infestans (Klug, 1834)¹³; however, other species of triatomines can maintain the transmission cycle of disease⁹. In this country, 65 species of triatomines have been identified¹⁴, including Panstrongylus megistus (Burmeister, 1835), Triatoma sordida (Stal, 1964), T. brasiliensis (Neiva, 1911), and Triatoma pseudomaculata (Corrêa & Espínola, 1964), and the main vector is T. cruzi¹⁵-¹⁷. In the Northeastern region, T. brasiliensis and T. pseudomaculata colonize both households and surrounding areas, thus maintaining the endemic cycle¹⁸,¹⁹. Moreover, Silva et al. collected triatomines in the Pernambuco State from 2013 to 2015 and recorded 10 species; however, only T. brasiliensis and P. lutzi (Neiva & Pinto, 1923) were positive for the T. cruzi²⁰ disease.

These findings indicate the need for eco-epidemiological studies that evaluate the transmission of T. cruzi by natural species, including studies that map regions according to the risk of vector transmission to better develop control strategies for public health. It is fundamental to gain knowledge regarding the distribution of triatomine fauna in endemic areas for Chagas disease in order to create relevant medical and public health guidelines. Therefore, this study aimed to analyze the spatial pattern of the natural infection index (NII) for triatomines and the risk of Chagas disease transmission in an endemic area of Northeastern Brazil.

MATERIALS AND METHODS

Study design

This was an ecological study that evaluated the distribution of triatomines, in an endemic area, for Chagas disease, namely the Pernambuco State, which is located in Northeastern Brazil¹⁷.

Study area

Pernambuco State has a territorial extent of 98,076,001 km², with an estimated population of 9,616,621 as of 2020²¹. This state has 184 municipalities and a state district (the island of Fernando de Noronha) and is divided into five mesoregions²¹ (Figure 1).

Figure 1
Map of the mesoregions of the Pernambuco State.

The Recife Metropolitan Area comprises 14 municipalities and has approximately 4,103,780 inhabitants, with an average urbanization rate of 86%. This region has a tropical and humid climate, and the predominant biome is the Atlantic Forest²². Zona da Mata region comprises 43 municipalities and has approximately 1,318,264 inhabitants, with an average urbanization rate of 62%. This region has a humid climate, and the predominant biome is the Atlantic Forest²².

The Agreste region comprises 71 municipalities and has approximately 2,172,963 inhabitants, with an average urbanization rate of 68%; the climate is humid in areas closer to the coast and arid in areas closer to Sertao. The biome presents a transition from the Atlantic Forest to the Caatinga²².

The Sertao do Sao Francisco region comprises 15 municipalities, has approximately 434,713 inhabitants, with an urbanization rate of 47%, and a semi-arid climate²². Finally, the Sertao region has 41 municipalities and approximately 571,071 inhabitants, with an urbanization rate of 26%. The predominant vegetation is the Caatinga, reflecting the hot and dry climate of the region²².

The Fernando de Noronha District was excluded from the current evaluation because it is an archipelago and does not present a relationship of contiguity or spatial adjacency with the municipalities of the state.

Study population and variables

From January 2016 to December 2018, triatomines were collected from houses/intradomicile and their vicinity/peridomicile (chicken coops, animal pens, stone walls, fences, rubble) by health agents of the respective municipalities. The insects were collected manually by municipal officers in household environments, in both urban and rural areas, using entomological tweezers. When required, lanterns and dislodging agents (Piriza 2%) were used. In the Pernambuco State, for two long decades, the insecticide Alpha-cypermethrin and the dislodging agent Piriza^® have been used¹⁷.

All insects were identified taxonomically and underwent a parasitological examination in entomology laboratories in one of the 12 health regions in Pernambuco State. All infected triatomines and 40% of non-infected insects were analyzed in the Laboratory for Endemic Diseases in Recife Municipality¹⁷.

The triatomines were identified at the species level in accordance with the classifications presented by Lent and Wygodzinsky²³, Galvão⁶ and Galvão and Gurgel-Gonçalves¹⁴. Parasitological research was performed using abdominal compression and subsequent parasitological studies of the fresh contents of the intestines. Parasite phenotypes (i.e., flagellates similar to T. cruzi, identified as natural infections by Trypanosoma sp.) were identified through observation under an optical microscope using Giemsa-stained insect feces. These insects arrived in the laboratory intact, but almost lifeless upon arrival due to the distances between laboratories¹⁷,²³.

The following variables were considered in this analysis: municipalities, number of captured insects and their life stages/characteristics (males, females, nymphs and not classified according to biological phase), collection sites (homes or surrounding areas), triatomine species, and number of infected insects. The NII was calculated according to the following formula developed by the Pan-American Health Organization and Brazilian Ministry of Health in 2003²⁴. The NII = (total number of infected triatomines/total number of insects examined) × 100.

The population data and the cartographic base of the municipalities were obtained in shapefile format from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE), which provides data in the form of a geographic projection system¹⁷ (latitude/longitude) and geodetic system (SIRGAS 2000); these data are available on the IBGE website²².

Data management and analysis

Spatial autocorrelation was evaluated using Global Moran Index (I), which tests the spatial dependence among observations. I > 0 indicates that standard deviations from the average are positive, thus showing direct correlation (clustering) between neighbors. When I < 0, standard deviations indicate negative or inverse correlations (i.e., dispersion). Finally, when I = 0, there is no spatial autocorrelation (i.e., randomness is observed)²⁵.

In addition, the local indicators produce a specific value for each area, thus allowing for the identification of groupings. Local Moran Index (II) (also known as Local Indicator for Spatial Autocorrelation [LISA]) is a spatial association indicator that evaluates the existence of clusters in the spatial arrangement of a given variable. This allows the detection of municipalities with spatial dependencies that are not illustrated through global indices²⁶. Four types of maps were used in the Moran autocorrelation test: i) a map of raw NII; (ii) a BoxMap map showing clusters with high–high patterns (i.e., areas where a specific municipality and its neighbors show high NII values), low-low patterns (i.e., areas where a specific municipality and its neighbors show low NII values), low-high patterns (i.e., areas where a specific municipality has a low NII and its neighbors have a high NII), and high-low patterns (i.e., areas where a specific municipality has a high NII and its neighbors have a low NII); (iii) a MoranMap map showing statistically significant high-high, low-low, low-high, and high-low clusters; and (iv) a LISA Cluster Map indicating the magnitude of the p-value for each municipality, with statistical significance defined according to a two-sided threshold of p < 0.05.

Spatial relative risk analysis was performed using spatial scan statistics. A Poisson model was used wherein the number of events in each area was considered to be distributed according to the population at known risk. The scan window coverage radius was set at 50% of the total population²⁶.

We used the following software programs for processing, analyzing, and calculating the spatial autocorrelation indicators and constructing thematic maps: Microsoft Excel (Microsoft, Seattle, WA, USA), SPSS statistical software (version 21.0, IBM, Armonk, NY, USA), QGIS (version 3.10.8, QGIS, Rimouski, Quebec, Canada), GeoDa (version 1.14.0, Geoda, Tel Aviv, Israel), and SaTScan (version 9.6, SaTScan, Boston, MA, USA).

Ethics statement

The study was approved by the Research Ethics Committee of the Hospital Complex HUOC/PROCAPE, Pernambuco State (CAAE 88154818.6.0000.5192).

RESULTS

In total, 7,302 triatomines (seven species) were captured in 99 different municipalities. The triatomines were primarily found in intradomicilary areas, including 6,001 adults (3,249 males and 2,752 females), 1,276 nymphs, and 25 triatomines were unclassified because they arrived at the laboratory in a condition that prevented identification, so they were only classified in terms of biological phase. Table 1 shows that the average NNI was 12% among the five infected species of triatomines; the most frequently infected species were P. lutzi (21%) and P. megistus (18%).

Table 1
Natural infection index for Trypanosoma sp. based on triatomines examined in the Pernambuco State from 2016 to 2018.

Species	Total insects examined		Intradomicile		Peridomicile		Positive
	N	%	N	%	N	%	N	%
T. brasiliensis	3,844	53%	3,585	93.50%	259	6.50%	395	10.50%
T. pseudomaculata	1,828	25%	1,733	95%	95	5%	159	8.70%
P. lutzi	1,366	18.50%	1,233	90.50%	133	9.50%	285	21%
P. megistus	162	2.20%	142	87.50%	20	12.50%	29	18%
T. sordida	45	0.60%	41	92%	4	8%	-	-
T. petrocchiae 1	44	0.50%	34	77.50%	10	22.50%	-	-
R. nasutus 2	13	0.20%	11	84.50%	2	15.50%	1	7.50%
Total	7,302	100%	6,779	93%	523	7%	869	12.00%

• ¹T. petrocchiae (Pinto & Barreto, 1925); ²R. nasutus (Stal, 1859)

Three species of triatomines, T. brasiliensis, T. pseudomaculata and P. lutzi were distributed in a greater number of municipalities than the other species in the study (Figure 2). The highest NNI values were found in the Agreste, Sertao do Sao Francisco, and Sertao mesoregions. The presence of a single infected R. nasutus specimen was noteworthy in Sertao.

Figure 2
Locations from where triatomines species were captured in the Pernambuco State, Northeastern Brazil, 2016–2018

The Agreste, Sertao, and Sao Francisco regions had the highest frequency of triatomines found inside households (Figure 3A). Among these regions, triatomines were collected in greater numbers in the Agreste and Sertao regions (Figure 3B). Zone 2 (i.e., west of the Agreste and east of Sertao) presented a relative risk of 3.65 compared to other areas of the state (Figure 4).

Figure 3
Prevalence map of triatomines captured in the intradomicile and peridomicile in the Pernambuco State, Northeastern Brazil, 2016–2018: A) triatomines captured in the intradomicile; B) triatomines captured in the peridomicile.

Figure 4
Spatial cluster classification: natural infection index for triatomines in the Pernambuco State, Northeastern Brazil, 2016–2018.

The following municipalities had the highest NII values (Figure 5): Zona da Mata, Agreste, Sertao, and Sertao do Sao Francisco. The I value was positive (0.2) and statistically significant (p = 0.01), indicating the existence of spatial correlation. In the BoxMap, the municipalities with the highest rates of infection were concentrated in the Zona da Mata, Agreste, and Sertao areas (Figure 5B). These areas showed statistical significance in the MoranMap and LISA Cluster Map, thereby identifying infection clusters in the Agreste and Sertao regions (Figures 5C and 5D).

Figure 5
Moran autocorrelation map showing natural infection index in the Pernambuco State, Northeastern Brazil, 2016–2018.

DISCUSSION

In this study, seven species of triatomines were found in four mesoregions of the Pernambuco State. The highest NII values were detected in three mesoregions, and natural infections were detected in five species of triatomines. The results of the study suggest that the risk of infected triatomines is approximately three times higher in the Agreste and Sertao regions than in the other areas studied here.

We detected in this study a higher presence of adult males compared to adult females or nymphs. The presence of nymphs among the collected species characterizes the adaptation of triatomines to household environments with regard to consolidating the colonization process. The nymphs may have been found in fewer numbers due to the low sensitivity of the method. In Brazil, this process is directly related to the endemicity of Chagas disease²⁷,²⁸.

The T. brasiliensis and T. pseudomaculata species were the most frequent in the study, indicating their vector potential in endemic regions, especially in or near households in rural areas²,²⁹. In our study, these vectors were naturally infected in the Agreste and Sertao regions; these results are consistent with results from other studies conducted in Northeastern Brazil²⁹,³⁰.

Ceccarelli et al. showed that the number of triatomines in Argentina post-2000 has almost tripled compared to the numbers indicated in the records prior to 2000, which were mainly collected in the dry and humid areas of Chaco (approximately 15,000 insects were collected in 100 years). Although the T. infestans species was present in Argentina, there was no record of P. megistus in this country³¹.

In our study, 7,302 vector insects were collected between January 2016 and December 2018; however, we detected only a small number of P. megistus. This result corroborates results of previous studies conducted in the Northeastern region²⁹,³⁰ and differs from studies conducted in the Southeastern³² and Southern regions of Brazil¹⁶. This may be related to the chemical control used to eliminate triatomines in the household environments in the various regions³³; however, the NNI for Trypanosoma sp. (18%) shows its vector capacity.

More than 1,500 triatomines were collected in a previous study conducted in the United States. The triatomines were predominantly collected in Texas and showed an NII of 54%; the two most frequently detected species were Triatoma gerstaeckeri (Stål, 1859) and Triatoma sanguisuga (Leconte, 1855)⁴. The triatomine species found in the United States are almost exclusively wild⁴, unlike those found in Central America³³ and South America³¹,³⁴.

In these regions, triatomines are found indoors; this is a similar result to our findings showing that 6,779 (93%) triatomines were collected inside homes. In our study, the highest NII rates, with regard to Trypanosoma sp., were found in P. lutzi (21%) and P. megistus (18%); however, T. brasiliensis, T. pseudomaculata, and P. lutzi showed the greatest spatial distribution. Barreto et al.³⁵ previously identified that P. lutzi was responsible for the highest rate of natural infections among the triatomines captured, although this species was found to only represent a small proportion of triatomines in Northeastern Brazil as a whole³⁵. The highest occurrence of P. megistus was recorded in the Paraná State, with an infection rate by T. cruzi of 19.7%¹⁶. The findings of these studies corroborate the present findings by showing that P. lutzi and P. megistus have vector importance in an endemic area of Chagas disease in Brazil¹⁷,³⁵.

Silva et al.²⁰ demonstrated the presence of eight species of triatomines distributed across Pernambuco, although natural infection was identified exclusively in T. brasiliensis and P lutzi. In our study, five naturally infected species were found, thus representing three additional species (T. pseudomaculata, P. megistus, and R. nasutus) compared to those identified in the 2013-2015 study. T. sordida was identified in only one municipality, but it was not infected. Only one specimen of R. nasutus, which was present in five other municipalities, showed natural infection. T. petrocchiae was the most colonized species in areas surrounding houses; however, no specimens were infected.

Between 2011 and 2014, 140 triatomines of four different species (100 Triatoma vitticeps [Stal, 1859], 25 Panstrongylus geniculatus [Latreille, 1811], eight P. megistus, and seven Triatoma arthurneivai [Lent and Martins,1940] specimens) were identified in Southeastern Brazil, with a highly heterogeneous spatial pattern evidenced in urban areas³². Among the insects collected in a previous study, P. megistus did not show a record of natural infection with Trypanosoma sp.³² (unlike in the present study). More specifically, in our study, the species showed natural infection in the hinterland and wilderness areas. This condition may explain why infested households were located closer to open fields.

P. lutzi was found to be spread across four mesoregions; the Metropolitan region was the only region with no records of this species. Previous studies¹⁷,²⁹ conducted in Northeastern Brazil have reported the presence of this species mainly in the semi-arid regions of the Agreste region, with its absence noted in the coastal areas; these findings are similar to our findings, and the species is still considered wild²,¹⁷. In contrast, R. nasutus was found in municipalities in Sertao, with a single record of positivity in our study. This finding is consistent with previous studies demonstrating its presence in semi-arid areas and the Caatinga biome¹⁷,²⁹.

Only one specimen of T. sordida was collected in the mesoregion of Sertao do Sao Francisco. However, no record of positivity was found in this species, despite it being the most frequently detected species in the arid and semi-arid regions of Brazil²⁹, as well as in Argentinian and Bolivian Chaco³¹,³⁶. It is possible that this finding is due to the fact that T. sordida is considered a secondary species in Northeastern Brazil, except in the Bahia State, in which there is a high frequency of this species¹⁹; this state borders the Pernambuco State municipality where this species was found. The macroecology of Chagas disease vectors is based on the distribution of geographical regions that present suitable environmental conditions for most triatomine species and are considered areas with an elevated risk of the disease due to the high number of infections with T. cruzi in the human population.

Spatial analysis conducted in our study identified a spatial autocorrelation in the Agreste and Sertao regions and a three-fold increased risk of finding naturally infected triatomines in these two areas than in other areas of the state. The vector geographical distribution is associated with regions of poverty and its transmission occurs with greater frequency in populations residing in poorly built, finished and maintained houses, commonly observed in rural areas of endemic countries in Latin America³⁷, and it is not found in large urban centers that exist in the coastal and forest regions of the Pernambuco State¹⁷. The physiogeographic characteristics of these areas (Zone 2) are favorable for the presence of the triatomine species typical of the semi-arid territory and the Caatinga. The activities that constitute the primary sector of the economy of the Sertao and Agreste regions (i.e., livestock and subsistence agriculture) are conducted in an area with a high density of triatomines, thereby enabling the presence of these vector species in households and surrounding niches³⁰,³⁵. The municipalities with higher mortality rates also showed the highest rates of chronic diseases, with patterns of homogeneity observed in the Zona da Mata and Sertao³⁸ regions.

Our study demonstrates the need for health services to be alerted regarding the possible occurrence of acute cases of Chagas disease in the Agreste and Sertao regions. Thus, gaining knowledge of the spatial dynamics of these vectors is of paramount importance. This study also highlights the use of geotechnologies, especially in analyses involving environmental and epidemiological factors, wherein spaces are integral to the processes of disease diffusion; this allows for better characterization and quantification of exposure and its possible results with regard to health consequences³⁵. Therefore, our findings contribute to the understanding of the structure of vector eco-epidemiology in space, allowing physicians and research scientists to interpret the distribution of health events and associated information with respect to the evaluation and prioritization of control programs for Chagas disease.

Information from the surveillance of Chagas disease vectors currently contributes to the identification of the epidemiological status of a given area. However, the findings of the study should be interpreted with caution, owing to the limitations due to the use of secondary data, which may lead to inconsistencies in the quantity and quality of information processing. However, to minimize the limitations of the study, duplication, incompleteness, and inconsistency were analyzed in the notification process and controlled by cleaning the database. Quality control is carried out by the Laboratory for Endemic Diseases at the central level of triatomines, sent by the laboratories of the municipalities. The impact was that, for the first time, a study with both spatial analysis and risk of areas of natural infection by T. cruzi was carried out, and these findings are important for decision-making in the entomological surveillance governmental program.

CONCLUSION

Our study shows potential areas of vector transmission of Chagas disease in the Pernambuco State. In this study, the application of different spatial analysis methods made it possible to locate these areas, which would not have been identified only by applying epidemiological indicators. Seven species of triatomines were found in the state. However, the highest NNI values were detected in three mesoregions. The most infected species were P. lutzi (21%) and P. megistus (18%), whereas the species with the greatest spatial distribution were T. brasiliensis, T. pseudomaculata, and P. lutzi. We conclude that there is an approximately three-fold increased risk of infected triatomines in a cluster of two areas (the Agreste and Sertao regions) than in the other regions evaluated in our study.

REFERENCES

• ¹
  World Health Organization. Chagas disease (also known as American trypanosomiasis). [cited 2023 Feb 23]. Available from: https://www.who.int/news-room/fact-sheets/detail/chagas-disease-(american-trypanosomiasis)
  » https://www.who.int/news-room/fact-sheets/detail/chagas-disease-(american-trypanosomiasis)
• ²
  Melo CM, Cruz AC, Lima AF, Silva LR, Madi RR, Lourdes SJ, et al. Triatomine fauna and recent epidemiological dynamics of Chagas disease in an endemic area of Northeast Brazil. Can J Infect Dis Med Microbiol. 2018;1018:7020541.
• ³
  Pérez-Mazliah D, Ward AI, Lewis MD. Host-parasite dynamics in Chagas disease from systemic to hyper-local scales. Parasite Immunol. 2021;43:e12786.
• ⁴
  Curtis-Robles R, Hamer SA, Lane S, Levy MZ, Hamer GL. Bionomics and spatial distribution of triatomine vectors of trypanosoma cruzi in Texas and other southern states, USA. Am J Trop Med Hyg. 2018;98:113-21.
• ⁵
  Eberhard FE, Cunze S, Kochmann J, Klimpel S. Modelling the climatic suitability of Chagas disease vectors on a global scale. elife. 2020;9:e52072.
• ⁶
  Galvão C. Taxonomia dos vetores da doença de Chagas: da forma à molécula, quase três séculos de história. In: Oliveira J, Alevi KC, Camargo LM, Meneguetti DU, organizadores. Atualidades em medicina tropical no Brasil: vetores. Rio Branco: Stricto Sensu; 2020. p.9-37.
• ⁷
  Alevi KC, Oliveira J, Silva Rocha D, Galvão C. Trends in taxonomy of chagas disease vectors (Hemiptera, reduviidae, triatominae): from linnaean to integrative taxonomy. Pathogens. 2021;10:1627.
• ⁸
  Oliveira Correia JP, Gil-Santana HR, Dale C, Galvão C. Triatoma guazu lent and Wygodzinsky is a junior synonym of Triatoma williami Galvão, Souza, and Lima. Insects. 2022;13:591.
• ⁹
  Monteiro FA, Weirauch C, Felix M, Lazoski C, Abad-Franch F. Evolution, systematics, and biogeography of the Triatominae, vectors of Chagas disease. Adv Parasitol. 2018;99:265-344.
• ¹⁰
  Gorla DE, Xiao-Nong Z, Diotaiuti L, Khoa PT, Waleckx E, Souza RC, et al. Different profiles and epidemiological scenarios: past, present and future. Mem Inst Oswaldo Cruz. 2022;117:e200409.
• ¹¹
  Waleckx E, Gourbière S, Dumonteil E. Intrusive versus domiciliated triatomines and the challenge of adapting vector control practices against Chagas disease. Mem Inst Oswaldo Cruz. 2015;110:324-38.
• ¹²
  Paiva VF, Belintani T, Oliveira J, Galvão C, Rosa JA. A review of the taxonomy and biology of Triatominae subspecies (Hemiptera: Reduviidae). Parasitol Res. 2022:121:499-512.
• ¹³
  Coura JR. The main sceneries of Chagas disease transmission: the vectors, blood and oral transmissions: a comprehensive review. Mem Inst Oswaldo Cruz. 2015;110:277-82.
• ¹⁴
  Galvão C, Gurgel-Gonçalves R. Vetores conhecidos no Brasil. In: Galvão C, organizador. Vetores da doença de Chagas no Brasil. Curitiba: Sociedade Brasileira de Zoologia; 2014. p.88-170.
• ¹⁵
  Bezerra CM, Barbosa SE, Souza RC, Barezani CP, Gürtler RE, Ramos AN Jr, et al. Triatoma brasiliensis Neiva, 1911: food sources and diversity of Trypanosoma cruzi in wild and artificial environments of the semiarid region of Ceará, Northeastern Brazil. Parasit Vectors. 2018;11:642.
• ¹⁶
  Ferro e Silva AM, Sobral-Souza T, Vancine MH, Muylaert RL, Abreu AP, Pelloso SM, et al. Spatial prediction of risk areas for vector transmission of Trypanosoma cruzi in the State of Parana. PLoS Negl Trop Dis. 2018;12:e0006907.
• ¹⁷
  Silva MB, Barreto AV, Silva HA, Galvão C, Rocha D, Jurberg J, et al. Synanthropic triatomines (Hemiptera, Reduviidae) in the state of Pernambuco, Brazil: geographical distribution and natural Trypanosoma infection rates between 2006 and 2007. Rev Soc Bras Med Trop. 2012;45:60-5.
• ¹⁸
  Parente CC, Bezerra FS, Parente PI, Dias-Neto RV, Xavier SC, Ramos AN, et al. Community-based entomological surveillance reveals urban foci of Chagas disease vectors in Sobral, State of Ceará, Northeastern Brazil. PLoS One. 2017;12:e0170278.
• ¹⁹
  Ribeiro Jr G, Santos CG, Lanza F, Reis J, Vaccarezza F, Diniz C, et al. Wide distribution of Trypanosoma cruziinfected triatomines in the State of Bahia, Brazil. Parasit Vectors. 2019;12:604.
• ²⁰
  Silva MB, Menezes KR, Farias MC, Andrade MS, Victor CC, Lorosa ES, et al. Description of the feeding preferences of triatominae in the Chagas disease surveillance study for the state of Pernambuco, Brazil (Hemiptera: Reduviidae). Rev Soc Bras Med Trop. 2017;50:543-6.
• ²¹
  Instituto Brasileiro de Geografia e Estatística. Estimativas de população. [cited 2023 Feb 23]. Available from: https://www.ibge.gov.br/estatisticas-novoportal/sociais/populacao/9103-estimativas-depopulacao.html?=&t=downloads
  » https://www.ibge.gov.br/estatisticas-novoportal/sociais/populacao/9103-estimativas-depopulacao.html?=&t=downloads
• ²²
  Instituto Brasileiro de Geografia e Estatística. Brasil/Permabuco. [cited 2023 Feb 23]. Available from: https://cidades.ibge.gov.br/brasil/pe/pesquisa/23/25359
  » https://cidades.ibge.gov.br/brasil/pe/pesquisa/23/25359
• ²³
  Lent H, Wygodzisnky P. Revision of the Triatominae (Hemiptera, Reduviidae) and their significance as vectors of Chagas disease. Bull Am Mus Nat Hist. 1979;163:123-520.
• ²⁴
  Organización Panamericana de La Salud. Guía para muestreo em actividades de vigilancia y control vectorial de la enfermedad de Chagas. Montevideo: OPAS; 2003. [cited 2023 Feb 23]. Available from: https://www.paho.org/en/node/12029
  » https://www.paho.org/en/node/12029
• ²⁵
  Burrough PA, McDonnell RA. Principles of geographical information systems. Oxford: Oxford University Press; 1998.
• ²⁶
  Kulldorff M. A spatial scan statistic. Commun Stat Theory Methods 1997;26:1481-96.
• ²⁷
  Silveira AC, Feitosa VR, Borges R. Distribuição de triatomíneos capturados no ambiente domiciliar, no período 1975/83, Brasil. Rev Bras Malariol Doencas Trop. 1984;36:15-312.
• ²⁸
  Barbosa-Silva AN, Souza RC, Diotaiuti L, Aguiar LM, Câmara AC, Galvão LM, et al. Synanthropic triatomines (Hemiptera: Reduviidae): infestation, colonization, and natural infection by trypanosomatids in the State of Rio Grande do Norte, Brazil. Rev Soc Bras Med Trop. 2019;52:e20190061.
• ²⁹
  Santos JP, Guimarães LM, Lima IP, Batista FM, Carvalho-Costa FA, Santos-Mallet JR. Spatial distribution of synanthropic triatomines in Piaui State, Northeastern Brazil. Rev Inst Med Trop Sao Paulo. 2020;62:e57.
• ³⁰
  Ferreira AL, Santana MA, Santos LV, Monteiro DP, Campos JH, Sena LL, et al. Triatoma brasiliensis Neiva, 1911 and Triatoma pseudomaculata Corrêa and Espínola, 1964 (Hemiptera, Reduviidae, Triatominae) in rural communities in Northeast Brazil. Rev Inst Med Trop Sao Paulo. 2020;62:e74.
• ³¹
  Ceccarelli S, Balsalobre A, Cano ME, Canale D, Lobbia P, Stariolo R, et al. Analysis of Chagas disease vectors occurrence data: the Argentinean triatomine species database. Biodivers Data J. 2020;8:e58076.
• ³²
  Dias JV, Queiroz DR, Martins HR, Gorla DE, Pires HH, Diotaiuti L. Spatial distribution of triatomines in domiciles of an urban area of the Brazilian Southeast region. Mem Inst Oswaldo Cruz. 2016;111:43-50.
• ³³
  Weinberg D, Porcasi X, Lanfri S, Abril M, Scavuzzo CM. Spatial analyzes of triatomine infestation indices and their association to the actions of a Chagas disease program and environmental variables during a 5-year intervention period. Acta Tropica. 2018;188:41-9.
• ³⁴
  Badel-Mogollón J, Rodríguez-Figueroa L, Parra-Henao G. Spatio-temporal analysis of the biophysical and ecological conditions of Triatoma dimidiata (Hemiptera: Reduviidae: Triatominae) in the northeast region of Colombia. Biomedica. 2017;37:106-23.
• ³⁵
  Barreto MA, Cavalcanti MA, Andrade CM, Nascimento EG, Pereira WO. Entomological triatomine indicators in the state of Rio Grande do Norte, Brazil. Cien Saude Colet. 2019;24:1483-93.
• ³⁶
  Salm A, Gertsch J. Cultural perception of triatomine bugs and Chagas disease in Bolivia: a cross-sectional field study. Parasit Vectors. 2019;12:291.
• ³⁷
  Reis D, Monteiro WM, Bossolani GD, Teston AP, Gomes ML, Araújo SM, et al. Biological behaviour in mice of Trypanosoma cruzi isolates from Amazonas and Paraná, Brazil. Exp Parasitol. 2012;130:321-9.
• ³⁸
  Medeiros CA, Silva MB, Oliveira AL, Alves SM, Barros MN, Cavalcati MG, et al. Mapping the morbidity and mortality of Chagas disease in an endemic area in Brazil. Rev Inst Med Trop Sao Paulo. 2022;64:e5.

• FUNDING: This study was supported in part by the Pro-Reitoria de Pos Graduação, Pesquisa e Inovacao, Public Funding Notice for Stricto Sensu Postgraduate Studies at the University of Pernambuco, grant Nº APQ 12024/21, and the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior – Brazil (CAPES), Finance Code 001.

Publication Dates

• Publication in this collection
  21 Apr 2023
• Date of issue
  2023

History

• Received
  5 Nov 2022
• Accepted
  23 Feb 2023