Detection of Tuberculosis in Toddlers and its Risk Factor at East Perak Health Center Surabaya

Azzahrain, Alifa Salsabila; Afifah, Anisa Nur; Yamani, Laura Navika

doi:10.20473/jkl.v15i2.2023.92-98

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…While there is some evidence indicating a relationship between humidity and tuberculosis transmission, further research is still needed to fully understand the interaction between humidity and this disease. 20,22,[55][56][57] In this research, no correlation was found between rainfall and tuberculosis. However, during the period of 2013-2020, the presence of tuberculosis in Kolaka Regency tended to increase.…”

Section: Discussioncontrasting

confidence: 52%

The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

Tosepu,

Sani,

Effendy

et al. 2023

F1000Res

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Background Tuberculosis is one of the diseases that requires comprehensive treatment. This disease is highly contagious and can be transmitted through the air. Climate factors play a role in the increasing cases of tuberculosis. This study aimed to determine the correlation between climatic variables and TB in Kolaka District, Southeast Sulawesi Province, Indonesia, Methods This research was modeled using an autoregressive (AR) Bayesian model with three possible likelihoods; Gaussian, Poisson and Negative Binomial responses. Results Minimum temperature, a coefficient of 4.234 suggests that for every 1 degree increase in minimum temperature, there is an estimated increase of approximately four cases, assuming other variables remain constant. Maximum temperature, a coefficient of 17.851 suggests that for every 1 degree increase in maximum temperature, there is an estimated increase of around 17-18 cases, assuming other variables remain constant. Average temperature, a coefficient of 4.234 suggests that for every 1 degree increase in average temperature, there is an estimated increase of approximately four cases, assuming other variables remain constant. Humidity, a coefficient of -13.413 suggests that for every 1% increase in humidity, there is an estimated decrease of around 13 cases, assuming other variables remain constant. Rainfall, a coefficient of -0.327 suggests that for every 1 mm increase in rainfall, there is an estimated decrease of around 0.327 cases, assuming other variables remain constant. Light, a coefficient of -4.322 suggests that for every 1-hour increase in light duration, there is an estimated decrease of around four cases, assuming other variables remain constant. Conclusions Climate change has a significant impact on tuberculosis through temperature-related factors. These factors influence the prevalence, spread, and vulnerability to TB. Addressing these challenges requires a holistic approach involving adaptation planning. Strong public health systems and healthcare infrastructure can help mitigate the risks and impacts of climate change-related tuberculosis.

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Section: Discussioncontrasting

confidence: 52%

The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

Tosepu,

Sani,

Effendy

et al. 2023

F1000Res

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“…Tabel 2 menunjukan hasil diagnosis oleh tim ahli klinis dari IDI dan IDAI. (Aziz, 2018;Azzahrain, Alifa Salsabila & Yamani, 2023;Budiati & Khoirina, 2018;Rahmawati & Rosita, 2021).…”

Section: Gambar 2 Dokumentasi Pelaksanaan Kegiatanunclassified

Kegiatan Skrining TBC pada Balita Stunting sebagai Upaya Percepatan Eliminasi Tahun 2028 di Kota Semarang

Rakhmawati,

Miarso,

Safitri

et al. 2023

SJPKM

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Kasus TBC anak di Kota Semarang hingga Januari 2023 terdapat 140 kasus (32,56%). Anak dengan kategori stunting memiliki risiko lebih tinggi untuk terpapar TBC. Status gizi terutama stunting pada anak berhubungan dengan daya tahan tubuh. Gejala TBC pada anak stunting seperti anoreksia, muntah, batuk, demam, dan penurunan berat badan. Bahaya TBC pada balita stunting terlihat pada peningkatan kerentanan terhadap infeksi, status gizi yang terganggu, dan potensi konsekuensi psikososial. Sangat penting untuk memprioritaskan kegiatan skrining TBC pada balita stunting, deteksi dini, dan pengobatan segera untuk mengurangi bahaya ini. Tujuan pengabdian masyarakat ini adalah sebagai Upaya Penemuan kasus TBC Anak, dan penemuan kasus ILTB untuk diberikan TPT. kegiatan dilakukan selama 4 hari yang dibagi 2 hari pemeriksaan dan 2 hari pembacaan TST (tuberculin skin test). Kegiatan dilakukan di aula kelurahan Mijen dengan sasaran anak dibawah 5 tahun yang berada di wilayah kerja puskesmas Mijen, Karangmalang, Ngaliyan, dan Purwoyoso. Kegiatan ini bermitra dengan IDI, IDAI, dan Udinus. Jumlah balita yang datang 149 balita, 16 balita tidak memiliki data antropometri (Berat Badan dan Tinggi Badan) yang lengkap. Berdasarkan pengukuran antropometri terdapat 111 (74,5%) balita stunting, 32 (21,5%) balita diantaranya positif TBC, 28 (25,22%) balita TBC Klinis, dan 7 (6,3%) balita TBC Laten. Balita positif TBC segera dilakukan inisiasi pengobatan dan pemantauan kepatuhan, dukungan nutrisi dan pemantauan pertumbuhan, dukungan psikososial dan pemantauan perkembangan yang dilakukan secara komprehensif

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The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

Tosepu,

Sani,

Effendy

et al. 2024

F1000Res

View full text Add to dashboard Cite

Background Tuberculosis is one of the diseases that requires comprehensive treatment. This disease is highly contagious and can be transmitted through the air. Climate factors play a role in the increasing cases of tuberculosis. This study aimed to determine the correlation between climatic variables and TB in Kolaka District, Southeast Sulawesi Province, Indonesia, Methods This research was modeled using an autoregressive (AR) Bayesian model with three possible likelihoods; Gaussian, Poisson and Negative Binomial responses. Results Minimum temperature and average temperature, a coefficient of 4.234 suggests that for every 1 degree increase in minimum temperature, there is an estimated increase of approximately four cases, assuming other variables remain constant. Maximum temperature, a coefficient of 17.851 suggests that for every 1 degree increase in maximum temperature, there is an estimated increase of around 17-18 cases, assuming other variables remain constant. Humidity, a coefficient of -13.413 suggests that for every 1% increase in humidity, there is an estimated decrease of around 13 cases, assuming other variables remain constant. Rainfall, a coefficient of -0.327 suggests that for every 1 mm increase in rainfall, there is an estimated decrease of around 0.327 cases, assuming other variables remain constant. Light, a coefficient of -4.322 suggests that for every 1-hour increase in light duration, there is an estimated decrease of around four cases, assuming other variables remain constant. Conclusions Climate change has a significant impact on tuberculosis through temperature-related factors. These factors influence the prevalence, spread, and vulnerability to TB. Addressing these challenges requires a holistic approach involving adaptation planning. Strong public health systems and healthcare infrastructure can help mitigate the risks and impacts of climate change-related tuberculosis.

show abstract

Detection of Tuberculosis in Toddlers and its Risk Factor at East Perak Health Center Surabaya

Cited by 5 publications

References 21 publications

The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

Kegiatan Skrining TBC pada Balita Stunting sebagai Upaya Percepatan Eliminasi Tahun 2028 di Kota Semarang

The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013–2020: a Bayesian autoregressive model

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