| Literature DB >> 36170270 |
Chanthawat Patikorn1, Jörg Blessmann2, Myat Thet Nwe3, Patrick Joseph G Tiglao4,5,6,7, Taksa Vasaruchapong8, Tri Maharani9, Uyen Vy Doan10, Syafiq Asnawi Zainal Abidin11, Ahmad Khaldun Ismail12, Iekhsan Othman11, Suthira Taychakhoonavudh1, Nathorn Chaiyakunapruk13,14,15.
Abstract
BACKGROUND: Understanding the burden of snakebite is crucial for developing evidence-informed strategies to pursue the goal set by the World Health Organization to halve morbidity and mortality of snakebite by 2030. However, there was no such information in the Association of Southeast Asian Nations (ASEAN) countries.Entities:
Mesh:
Substances:
Year: 2022 PMID: 36170270 PMCID: PMC9518918 DOI: 10.1371/journal.pntd.0010775
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Estimated annual disease burden of snakebite in ASEAN countries.
| Snakebite victims, n | Antivenom indicated victims, n | Deaths, n | Amputations, n | YLLs | YLDs | DALYs | DALYs per 100,000 population | |
|---|---|---|---|---|---|---|---|---|
|
| 3,412 (3,303–3,533) | 481 (254–767) | 2 (0–6) | 0 | 50 (0–151) | 1.4 (0.6–2.5) | 52 (1–152) | 0.2 (0.003–0.5) |
|
| 8,715 (8,525–8,906) | 5,166 (3,766–6,482) | 4 (2–7) | 2 (0–7) | 102 (51–178) | 8 (4–14) | 110 (57–185) | 0.2 (0.1–0.3) |
|
| 135,000 (134,297–135,689) | 49,632 (34,229–65,496) | 10,547 (5,012–22,563) | 799 (355–1,426) | 262,302 (124,650–561,145) | 586 (246–1,120) | 262,888 (125,252–562,144) | 97 (46–208) |
|
| 13,377 (11,452–15,772) | 1,755 (1,457–2,127) | 550 (274–1,099) | 12 (6–16) | 13,311 (6,624–26,641) | 7 (4–11) | 13,320 (6,632–26,649) | 12 (6–25) |
|
| 46,745 (17,500–91,013) | 41,236 (15,290–80,701) | 1,655 (490–4,440) | 0 | 40,136 (11,869–107,679) | 114 (38–258) | 40,250 (11,931–107,876) | 42 (12–112) |
|
| 14,339 (14,111–14,571) | 3,029 (2,917–3,138) | 1,007 (510–2,009) | 141 (22–348) | 24,468 (12,420–48,837) | 61 (10–189) | 24,532 (12,462–48,880) | 342 (174–682) |
|
| 21,059 (20,623–21,540) | 16,275 (15,877–16,679) | 2,145 (1,303–3,824) | 0 | 50,786 (30,877–90,632) | 44 (27–67) | 50,830 (30,926–90,673) | 94 (57–168) |
|
| 242,648 (209,810–291,023) | 117,575 (73,790–175,390) | 15,909 (7,592–33,949) | 954 (383–1,797) | 391,154 (186,491–835,263) | 825 (329–1,661) | 391,979 (187,261–836,559) | 61 (29–131) |
Estimates are presented as base-case estimates with their 95% credibility interval (in parentheses) based on probabilistic sensitivity analysis. Abbreviations: DALYs–disability-adjusted life years; YLDs–years lived with disabilities; YLLs–years of life lost
* input parameters were based on national statistics and published literature
¶ Input parameters were based on published literature and anecdotal evidence
+ Input parameters were based on anecdotal evidence.
Estimated annual economic burden (x1,000 USD) of snakebite in ASEAN countries.
| Direct medical costs, x1,000 USD | Direct non-medical costs, x1,000 USD | Indirect costs, x1,000 USD | Total costs, x1,000 USD | Total costs, % of GDP | |||||
|---|---|---|---|---|---|---|---|---|---|
| Healthcare costs | Antivenom-related costs | Amputation costs | Transportation costs | Additional food costs | Productivity losses during Snakebit episode | Productivity losses due to Premature death | |||
|
| 754 (620–932) | 475 (249–758) | 0 | 38 (34–42) | 29 (23–40) | 366 (289–484) | 622 (0–1,866) | 2,284 (1,380–3,736) | 0.001% (0.000–0.001%) |
|
| 2,027 (1,615–2,531) | 1,176 (844–1,506) | 0.2 (0–0.6) | 58 (54–64) | 50 (37–67) | 925 (702–1,190) | 762 (381–1,333) | 4,999 (3,861–6,260) | 0.001% (0.001–0.001) |
|
| 51,836 (36,900–70,844) | 4,129 (3,727–4,520) | 100 (44–178) | 1,579 (1,431–1,738) | 1,442 (1,027–1,970) | 8,752 (6,506–11,566) | 1,922,241 (914,489–4,110,887) | 1,988,891 (975,513–4,202,049) | 0.178% (0.087–0.375%) |
|
| 444 (338–578) | 147 (130–162) | 1 (1–2) | 63 (52–76) | 46 (35–60) | 638 (518–793) | 81,905 (40,762–163,735) | 83,244 (42,165–165,246) | 0.022% (0.011–0.044%) |
|
| 3,208 (1,090–7,137) | 1,094 (447–1,210) | 0 | 853 (299–1,874) | 1,463 (494–3,264) | 3,801 (1,320–8,251) | 257,594 (76,180–690,928) | 268,013 (82,106–710,764) | 0.102% (0.031–0.271%) |
|
| 55 (42–71) | 27 (23–32) | 12 (2–34) | 13 (12–15) | 16 (13–20) | 427 (361–501) | 80,031 (40,573–159,767) | 80,583 (41,188–160,291) | 0.443% (0.227–0.882%) |
|
| 1,382 (1,047–1,815) | 2,159 (1,910–2,425) | 0 | 474 (417–526) | 394 (303–516) | 1,208 (952–1,551) | 73,569 (44,703–131,172) | 79,186 (50,302–136,615) | 0.104% (0.066–0.180%) |
|
| 59,706 (41,652–83,950) | 9,208 (7,329–10,613) | 114 (46–215) | 3,078 (2,299–4,335) | 3,441 (1,932–5,938) | 16,117 (10,648–24,335) | 2,416,724 (1,117,087–5,259,687) | 2,507,199 (1,196,516–5,384,962) | 0.091% (0.043–0.195%) |
Estimates are presented as base-case estimates (x 1000 USD) with their 95% credibility interval (in parentheses) based on probabilistic sensitivity analysis. Costs are presented as 2019 USD where 1 USD = 14,147.67 Indonesian Rupees = 51.80 Philippine Pesos = 23,050.24 Vietnamese Dong = 8,679.41 Lao Kip = 1,518.26 Myanmar Kyat. Abbreviation: GDP–gross domestic product; USD—US Dollar
* input parameters were based on national statistics and published literature
¶ Input parameters were based on published literature and anecdotal evidence
+ Input parameters were based on anecdotal evidence.