Entomological surveillance in Rio Grande do Norte (2005–2022)
Data files
Jun 15, 2026 version files 137.14 KB
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dados_triatomineos_RN_2005_2022.csv
125.12 KB
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README.md
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Abstract
This dataset compiles secondary data derived from entomological surveillance and vector control activities targeting triatomines conducted in the state of Rio Grande do Norte, Brazil, between 2005 and 2022. The data refer to triatomine captures in domiciliary units (DUs), including intradomiciliary and peridomiciliary environments, and were organized by mesoregion.
The database includes records of triatomine presence, the number of municipalities conducting entomological surveillance activities, identified species, and information related to natural infection by Trypanosoma cruzi, when available. The mesoregions included are the West, Central, and Agreste regions of Rio Grande do Norte. Municipalities from the Eastern mesoregion were not included due to the absence of systematized data during the analyzed period.
This dataset can be used for epidemiological and entomological analyses, spatial and temporal studies of triatomine distribution, risk assessment for vector-borne transmission of Chagas disease, and to support public health surveillance actions and scientific research.
Dataset DOI: 10.5061/dryad.c866t1gnt
Description of the data and file structure
This dataset compiles secondary data derived from entomological surveillance and vector control activities targeting triatomines conducted in the state of Rio Grande do Norte, Brazil, between 2005 and 2022. The data refer to triatomine captures in domiciliary units (DUs), including intradomiciliary and peridomiciliary environments, and were organized by mesoregion.
The database includes records of triatomine presence, the number of municipalities conducting entomological surveillance activities, identified species, and information related to natural infection by Trypanosoma cruzi, when available. The mesoregions included are the West, Central, and Agreste regions of Rio Grande do Norte. Municipalities from the Eastern mesoregion were not included due to the absence of systematized data during the analyzed period.
This dataset can be used for epidemiological and entomological analyses, spatial and temporal studies of triatomine distribution, risk assessment for vector-borne transmission of Chagas disease, and to support public health surveillance actions and scientific research.
Files and variables
File: dados_triatomineos_RN_2005_2022.csv
Description: This dataset contains annual entomological surveillance data on triatomine insects collected in the State of Rio Grande do Norte, Brazil, from 2005 to 2022. Data were obtained from routine entomological surveillance activities conducted at the municipal level and aggregated by municipality, year, and mesoregion. The dataset includes information on inspected households, household infestation, triatomine capture and examination, species distribution, intradomiciliary and peridomiciliary occurrence, developmental stage (adult/nymph), and natural infection indicators.
Variables
- unit: Unique row identifier (record ID) in the dataset spreadsheet
- year: Year of surveillance record
- mesoregion: Mesoregion of Rio Grande do Norte, Brazil
- 1 - Agreste
- 2 - Central
- 3 - West
- 4 - East
- municipality: Municipality number corresponding to municipalities of Rio Grande do Norte, Brazil
- 1 Barcelona
- 2 Bento Fernandes
- 3 Boa Saúde
- 4 Bom Jesus
- 5 Brejinho
- 6 Campo Redondo
- 7 Coronel Ezequiel
- 8 Ielmo Marinho
- 9 Jaçanã
- 10 Jandaíra
- 11 Japi
- 12 João Câmara
- 13 Jundiá
- 14 Lagoa d'Anta
- 15 Lagoa de Pedras
- 16 Lagoa de Velhos
- 17 Lagoa Salgada
- 18 Lajes Pintadas
- 19 Monte Alegre
- 20 Monte das Gameleiras
- 21 Nova Cruz
- 22 Parazinho
- 23 Passa-e-Fica
- 24 Passagem
- 25 Poço Branco
- 26 Riachuelo
- 27 Ruy Barbosa
- 28 Santa Cruz
- 29 Santa Maria
- 30 Santo Antônio
- 31 São Bento do Trairi
- 32 São José do Campestre
- 33 São Paulo do Potengi
- 34 São Pedro
- 35 São Tomé
- 36 Senador Elói de Souza
- 37 Serra Caiada
- 38 Serra de São Bento
- 39 Serrinha
- 40 Sítio Novo
- 41 Tangará
- 42 Várzea
- 43 Vera Cruz
- 44 Acari
- 45 Afonso Bezerra
- 46 Angicos
- 47 Bodó
- 48 Caiçara do Norte
- 49 Caiçara do Rio do Vento
- 50 Caicó
- 51 Carnaúba dos Dantas
- 52 Cerro Corá
- 53 Cruzeta
- 54 Currais Novos
- 55 Equador
- 56 Fernando Pedroza
- 57 Florânia
- 58 Galinhos
- 59 Guamaré
- 60 Ipueira
- 61 Jardim de Angicos
- 62 Jardim de Piranhas
- 63 Jardim do Seridó
- 64 Lagoa Nova
- 65 Lajes
- 66 Macau
- 67 Ouro Branco
- 68 Parelhas
- 69 Pedra Preta
- 70 Pedro Avelino
- 71 Santana do Matos
- 72 Santana do Seridó
- 73 São Bento do Norte
- 74 São Fernando
- 75 São João do Sabugi
- 76 São José do Seridó
- 77 São Vicente
- 78 Serra Negra do Norte
- 79 Tenente Laurentino Cruz
- 80 Timbaúba dos Batistas
- 81 Água Nova
- 82 Alexandria
- 83 Almino Afonso
- 84 Alto do Rodrigues
- 85 Antônio Martins
- 86 Apodi
- 87 Areia Branca
- 88 Assu
- 89 Baraúna
- 90 Campo Grande
- 91 Caraúbas
- 92 Carnaubais
- 93 Coronel João Pessoa
- 94 Doutor Severiano
- 95 Encanto
- 96 Felipe Guerra
- 97 Francisco Dantas
- 98 Frutuoso Gomes
- 99 Governador Dix-Sept Rosado
- 100 Grossos
- 101 Ipanguaçu
- 102 Itajá
- 103 Itaú
- 104 Janduís
- 105 João Dias
- 106 José da Penha
- 107 Jucurutu
- 108 Lucrécia
- 109 Luís Gomes
- 110 Major Sales
- 111 Marcelino Vieira
- 112 Martins
- 113 Messias Targino
- 114 Mossoró
- 115 Olho-d'Água do Borges
- 116 Paraná
- 117 Paraú
- 118 Patu
- 119 Pau dos Ferros
- 120 Pendências
- 121 Pilões
- 122 Portalegre
- 123 Porto do Mangue
- 124 Rafael Fernandes
- 125 Rafael Godeiro
- 126 Riacho da Cruz
- 127 Riacho de Santana
- 128 Rodolfo Fernandes
- 129 São Francisco do Oeste
- 130 São Miguel
- 131 São Rafael
- 132 Serra do Mel
- 133 Serrinha dos Pintos
- 134 Severiano Melo
- 135 Taboleiro Grande
- 136 Tenente Ananias
- 137 Tibau
- 138 Triunfo Potiguar
- 139 Umarizal
- 140 Upanema
- 141 Venha-Ver
- 142 Viçosa
- 143 Arez
- 144 Baía Formosa
- 145 Canguaretama
- 146 Ceará-Mirim
- 147 Espírito Santo
- 148 Extremoz
- 149 Goianinha
- 150 Macaíba
- 151 Maxaranguape
- 152 Montanhas
- 153 Natal
- 154 Nísia Floresta
- 155 Parnamirim
- 156 Pedra Grande
- 157 Pedro Velho
- 158 Pureza
- 159 Rio do Fogo
- 160 São Gonçalo do Amarante
- 161 São José de Mipibu
- 162 São Miguel do Gostoso
- 163 Senador Georgino Avelino
- 164 Taipu
- 165 Tibau do Sul
- 166 Touros
- 167 Vila Flor
- houses: Total number of domiciliary units (DUs) registered
- surveyed_houses: Total number of inspected domiciliary units (DUs)
- positive_houses: Total number of domiciliary units (DUs) positive for triatomines
- intradomiciliary_positive_houses: Total number of positive domiciliary units (DUs) with intradomiciliary infestation
- peridomiciliary_positive_houses: Total number of positive domiciliary units (DUs) with peridomiciliary infestation
- intradomiciliary_nymphs: Total number of nymphs detected in the intradomicile
- captured_insects: Total number of captured triatomines
- examined_insects: Total number of examined triatomines
- infected_insects: Total number of triatomines positive for Trypanosoma cruzi infection
- sprayed_houses: Total number of domiciliary units (DUs) sprayed with insecticide
- T_brasiliensis: Presence or absence of Triatoma brasiliensis in domiciliary units (DUs)
- 0 - Absence of Triatoma brasiliensis
- 1 - Presence of Triatoma brasiliensis
- T_brasiliensis_intra: Number of Triatoma brasiliensis specimens captured in the intradomiciliary environment per municipality
- T_brasiliensis_peri: Number of Triatoma brasiliensis specimens captured in the peridomiciliary environment per municipality
- T_brasiliensis_adult: Number of adult Triatoma brasiliensis specimens captured per municipality
- T_brasiliensis_nymph: Number of Triatoma brasiliensis nymphs captured per municipality
- T_pseudomaculata: Presence or absence of Triatoma pseudomaculata in domiciliary units (DUs)
- 0 – Absence of Triatoma pseudomaculata
- 1 – Presence of Triatoma pseudomaculata
- T_pseudomaculata_intra: Number of Triatoma pseudomaculata specimens captured in the intradomiciliary environment per municipality
- T_pseudomaculata_peri: Number of Triatoma pseudomaculata specimens captured in the peridomiciliary environment per municipality
- T_pseudomaculata_adult: Number of adult Triatoma pseudomaculata specimens captured per municipality
- T_pseudomaculata_nymph: Number of Triatoma pseudomaculata nymphs captured per municipality
- T_petrochiae: Presence or absence of Triatoma petrochiae in domiciliary units (DUs)
- 0 – Absence of Triatoma petrochiae
- 1 – Presence of Triatoma petrochiae
- T_petrochiae_intra: Number of Triatoma petrochiae specimens captured in the intradomiciliary environment per municipality
- T_petrochiae_peri: Number of Triatoma petrochiae specimens captured in the peridomiciliary environment per municipality
- T_petrochiae_adult: Number of adult Triatoma petrochiae specimens captured per municipality
- T_petrochiae_nymph: Number of Triatoma petrochiae nymphs captured per municipality
- R_nasutus: Presence or absence of Rhodnius nasutus in domiciliary units (DUs)
- 0 – Absence of Rhodnius nasutus
- 1 – Presence of Rhodnius nasutus
- R_nasutus_intra: Number of Rhodnius nasutus specimens captured in the intradomiciliary environment per municipality
- R_nasutus_peri: Number of Rhodnius nasutus specimens captured in the peridomiciliary environment per municipality
- R_nasutus_adult: Number of adult Rhodnius nasutus specimens captured per municipality
- R_nasutus_nymph: Number of Rhodnius nasutus nymphs captured per municipality
- P_lutz: Presence or absence of Panstrongylus lutzi in domiciliary units (DUs)
- 0 – Absence of Panstrongylus lutzi
- 1 – Presence of Panstrongylus lutzi
- P_lutz_intra: Number of Panstrongylus lutzi specimens captured in the intradomiciliary environment per municipality
- P_lutz_peri: Number of Panstrongylus lutzi specimens captured in the peridomiciliary environment per municipality
- P_lutz_adult: Number of adult Panstrongylus lutzi specimens captured per municipality
- P_lutz_nymph: Number of Panstrongylus lutzi nymphs captured per municipality
- infestation_index: Infestation index = (positive DUs / inspected DUs) × 100
- intradomiciliary_infestation_index: Intradomiciliary infestation index = (positive intradomiciliary DUs / inspected DUs) × 100
- peridomiciliary_infestation_index: Peridomiciliary infestation index = (positive peridomiciliary DUs / inspected DUs) × 100
- colonization_index: Colonization index = (DUs with intradomiciliary nymphs / positive intradomiciliary DUs) × 100
- overall_natural_infection_index: Natural infection index = (number of positive triatomines / number of examined triatomines) × 100
- natural_infection_T_brasiliensis: Natural infection index for Triatoma brasiliensis= (number of positive Triatoma brasiliensis/ number of examined triatomines) × 100
- natural_infection_T_pseudomaculata: Natural infection index for Triatoma pseudomaculata = (number of positive Triatoma pseudomaculata / number of examined triatomines) × 100
- natural_infection_P_lutzi: Natural infection index for Panstrongylus lutzi = (number of positive Panstrongylus lutzi / number of examined triatomines) × 100
- natural_infection_R_nasutus: Natural infection index for Rhodnius nasutus = (number of positive Rhodnius nasutus / number of examined triatomines) × 100
- natural_infection_T_petrochiae: Natural infection index for Triatoma petrochiae = (number of positive Triatoma petrochiae / number of examined triatomines) × 100
- Missing values: Missing or unavailable values are represented as blank cells
Code/software
The dataset is provided in Comma-Separated Values (CSV) format and can be accessed using spreadsheet software, such as Microsoft Excel (version 2016 or later).
Access information
Other publicly accessible locations of the data:
- Not applicable. The dataset is not publicly available from other sources.
Data was derived from the following sources:
- The dataset was derived from routine entomological surveillance records of triatomine insects conducted in the State of Rio Grande do Norte, Brazil, between 2005 and 2022.