Back Public health mitigation of COVID-19 English Mitigasi kesihatan awam COVID-19 Malay

Ragewan Jama'a Don COVID-19

Ragewan Jama'a Don COVID-19
Bayanai
Ƙaramin ɓangare na communicable disease control (en) Fassara, response to the COVID-19 pandemic (en) Fassara da mitigation (en) Fassara

Gudu da sikelin su ne mabuɗin don rage COVID-19, saboda yanayin haɗarin kamuwa da cuta mai kitse da haɓakar haɓakar cututtukan COVID-19.[1] Don ragewa ya yi tasiri, (a) dole ne a karya sarƙoƙin watsawa da wuri-wuri ta hanyar tantancewa da tsarewa, (b) dole ne a samar da kulawar lafiya don samar da buƙatun waɗanda suka kamu da cutar, kuma (c) dole ne a samar da abubuwan da suka dace. don ba da damar yin tasiri mai tasiri na (a) da (b).

Manufofin ragewa sun haɗa da jinkirtawa da rage nauyi mafi girma akan kiwon lafiya ( lalata lanƙwasa ) da rage yawan lokuta da tasirin lafiya.[2][3] Haka kuma, ci gaba da haɓaka ƙarfin kiwon lafiya ( ɗayan layi ) kamar ta hanyar haɓaka ƙidayar gado, ma'aikata, da kayan aiki, suna taimakawa wajen biyan buƙatu.[4]
Ƙoƙarin ragewa waɗanda ba su da isasshen ƙarfi ko tsawon lokaci-kamar shakatawa da wuri na ƙa'idodin nesanta kansu ko umarnin zama-a-na iya ba da damar sake dawowa bayan tiyata na farko da ragewa.[5][6]

Wani ɓangare na sarrafa barkewar cutar yana ƙoƙarin jinkirtawa da rage kololuwar annobar, wanda aka sani da karkatar da yanayin cutar.[7] Wannan yana rage haɗarin ayyukan kiwon lafiya da yawa kuma yana ba da ƙarin lokaci don haɓaka alluran rigakafi da jiyya. [8] Abubuwan da ba na magunguna ba waɗanda za su iya magance barkewar cutar sun haɗa da matakan kariya na mutum kamar tsabtace hannu, sanya abin rufe fuska, da keɓe kai; matakan al'umma da ke da niyya ta jiki kamar rufe makarantu da soke taron taron jama'a; haɗin gwiwar al'umma don ƙarfafa yarda da shiga cikin irin wannan shisshigi; da kuma matakan muhalli irin wannan tsaftacewa.[9] An kuma ba da shawarar cewa inganta samun iska da sarrafa tsawon lokacin bayyanarwa na iya rage watsawa.[10][11]

An dauki karin tsauraran matakai da nufin dakile barkewar cutar a China da zarar tsananin barkewar ya bayyana, kamar kebe daukacin biranen da kuma sanya dokar hana zirga-zirga.[12] Sauran kasashen kuma sun dauki matakai daban-daban da nufin takaita yaduwar cutar. Koriya ta Kudu ta gabatar da gwajin yawan jama'a da keɓe keɓe tare da ba da faɗakarwa kan motsin mutanen da suka kamu da cutar. Kasar Singapore ta ba da tallafin kudi ga wadanda suka kamu da cutar da suka kebe kansu tare da sanya tara masu yawa ga wadanda suka kasa yin hakan. Taiwan ta kara samar da abin rufe fuska da kuma azabtar da tarin kayayyakin kiwon lafiya.[13]

Kwaikwayo don Biritaniya da Amurka sun nuna cewa ragewa (hankali amma ba a daina yaɗuwar annoba ba) da murkushewa (mayar da ci gaban annoba) suna da manyan ƙalubale. Manufofin raguwa mafi kyau na iya rage buƙatun kiwon lafiya da kashi biyu bisa uku da mace-mace da rabi, amma har yanzu suna haifar da mutuwar ɗaruruwan dubunnan mutane da kuma mamaye tsarin kiwon lafiya. Ana iya fifita murkushewa amma yana buƙatar kiyayewa har tsawon lokacin da kwayar cutar ke yaduwa a cikin yawan mutane (ko har sai an sami allurar rigakafi), yayin da watsawar in ba haka ba da sauri ya sake dawowa lokacin da matakan suka huta. Har zuwa yanzu, shaidun ayyukan kiwon lafiyar jama'a (marasa magunguna) kamar nisantar da jama'a, rufe makarantu, da keɓewar shari'ar sun fito ne daga samfuran ɓangarori na annoba da, musamman, samfuran tushen wakilai (ABMs).[14] Irin waɗannan samfuran an soki su don kasancewa bisa sauƙi da zato marasa gaskiya.[15][16] Har yanzu, suna iya zama da amfani wajen sanar da yanke shawara game da ragewa da matakan murkushewa a lokuta lokacin da aka daidaita ABMs daidai.[17] Wani binciken ƙirar Argentina ya tabbatar da cewa za a iya guje wa cikakken kulle-kullen da tsarin kiwon lafiya idan aka gano kashi 45 na marasa lafiyar asymptomatic kuma an ware su. [18] Tsawon lokaci mai tsawo don murkushe cutar yana da tsadar zamantakewa da tattalin arziki.[19]

A cikin watan Agusta 2020, wata takarda aiki ta Ofishin Binciken Tattalin Arziƙi na Ƙasa (NBER) ta yi tambaya game da manyan illolin da yawa na raguwa da matakan murkushewa. Marubutan sun kwatanta ci gaban wadanda suka jikkata da ke da alaƙa da SARS-CoV-2 har zuwa Yuli 2020, a cikin jihohin Amurka 25 da ƙasashe 23 waɗanda suka ƙidaya sama da mutuwar 1.000 gabaɗaya. Daga ranar da wata jiha ta wuce iyakar mutuwar mutane 25, binciken kididdiga ya lura da ci gaba iri ɗaya, ba tare da nau'i da lokaci na hulɗar gwamnati ba. Don haka, yawan adadin wadanda suka mutu ya ragu zuwa sifili a cikin kwanaki 20-30, kuma bambancin dake tsakanin yankuna ya ragu, sai dai a farkon annoba. Marubutan sun lissafta ingantaccen lambar haifuwa R eff tare da taimakon samfura daban-daban kamar samfurin SIR, kuma sun same shi yana shawagi a kusa da ɗaya ko'ina bayan kwanaki 30 na farko na annobar. Don haka, ba su sami shaidar tasirin kulle-kulle ba, hana tafiye-tafiye ko keɓewa kan watsa kwayar cutar. [17] Don karatu masu karo da juna, suna ɗaukan ɓatanci mai canzawa . 'Yan takarar don tasirin da ba a kula da su ba na iya zama nisantar zamantakewa na son rai, tsarin hanyoyin sadarwar zamantakewa (wasu mutane suna tuntuɓar cibiyoyin sadarwa da sauri fiye da wasu), da kuma yanayin yanayi na annoba don yaɗuwa da sauri da farko kuma yana raguwa, wanda aka lura a cikin tsohon mura. annoba, amma har yanzu ba a gane gaba daya ba. Mai bita Stephen C. Miller ya kammala "cewa hulɗar ɗan adam ba ta dace da tsarin cututtuka masu sauƙi ba". [20] [21]

  1. ↑ Cirillo, Pasquale and Nassim Nicholas Taleb (2020). "Tail Risk of Contagious Diseases". Nature Physics. 16 (6): 606–613. arXiv:2004.08658. Bibcode:2020NatPh..16..606C. doi:10.1038/s41567-020-0921-x. S2CID 215828381.
  2. ↑ Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD (March 2020). "How will country-based mitigation measures influence the course of the COVID-19 epidemic?". Lancet. 395 (10228): 931–934. doi:10.1016/S0140-6736(20)30567-5. PMC 7158572. PMID 32164834. A key issue for epidemiologists is helping policy makers decide the main objectives of mitigation—e.g. minimising morbidity and associated mortality, avoiding an epidemic peak that overwhelms health-care services, keeping the effects on the economy within manageable levels, and flattening the epidemic curve to wait for vaccine development and manufacture on scale and antiviral drug therapies.
  3. ↑ Qualls N, Levitt A, Kanade N, Wright-Jegede N, Dopson S, Biggerstaff M, et al. (April 2017). "Community Mitigation Guidelines to Prevent Pandemic Influenza - United States, 2017". MMWR. Recommendations and Reports. 66 (1): 1–34. doi:10.15585/mmwr.rr6601a1. PMC 5837128. PMID 28426646.
  4. ↑ Barclay E, Scott D, Animashaun C (2020-04-07). "The US doesn't just need to flatten the curve. It needs to "raise the line."". Vox. Archived from the original on 2020-04-07.
  5. ↑ Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD (March 2020). "How will country-based mitigation measures influence the course of the COVID-19 epidemic?". Lancet. 395 (10228): 931–934. doi:10.1016/S0140-6736(20)30567-5. PMC 7158572. PMID 32164834. A key issue for epidemiologists is helping policy makers decide the main objectives of mitigation—e.g. minimising morbidity and associated mortality, avoiding an epidemic peak that overwhelms health-care services, keeping the effects on the economy within manageable levels, and flattening the epidemic curve to wait for vaccine development and manufacture on scale and antiviral drug therapies.
  6. ↑ Wiles S (2020-03-14). "After 'Flatten the Curve', we must now 'Stop the Spread'. Here's what that means". The Spinoff. Archived from the original on 2020-03-26. Retrieved 2020-03-13.
  7. ↑ Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD (March 2020). "How will country-based mitigation measures influence the course of the COVID-19 epidemic?". Lancet. 395 (10228): 931–934. doi:10.1016/S0140-6736(20)30567-5. PMC 7158572. PMID 32164834. A key issue for epidemiologists is helping policy makers decide the main objectives of mitigation—e.g. minimising morbidity and associated mortality, avoiding an epidemic peak that overwhelms health-care services, keeping the effects on the economy within manageable levels, and flattening the epidemic curve to wait for vaccine development and manufacture on scale and antiviral drug therapies.
  8. ↑ Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD (March 2020). "How will country-based mitigation measures influence the course of the COVID-19 epidemic?". Lancet. 395 (10228): 931–934. doi:10.1016/S0140-6736(20)30567-5. PMC 7158572. PMID 32164834. A key issue for epidemiologists is helping policy makers decide the main objectives of mitigation—e.g. minimising morbidity and associated mortality, avoiding an epidemic peak that overwhelms health-care services, keeping the effects on the economy within manageable levels, and flattening the epidemic curve to wait for vaccine development and manufacture on scale and antiviral drug therapies.
  9. ↑ "Community Mitigation Guidelines to Prevent Pandemic Influenza—United States, 2017". Recommendations and Reports. 66 (1). 2017-04-12.
  10. ↑ Epperly, David E.; Rinehart, Kristopher R.; Caney, David N. (2020). "COVID-19 Aerosolized Viral Loads, Environment, Ventilation, Masks, Exposure Time, Severity, And Immune Response: A Pragmatic Guide Of Estimates". medRxIv. doi:10.1101/2020.10.03.20206110.
  11. ↑ "Viral Load Exposure Factors". ReallyCorrect.com.
  12. ↑ Qin, Amy (2020-03-07). "China May Be Beating the Coronavirus, at a Painful Cost". The New York Times.
  13. ↑ McCurry J, Ratcliffe R, Davidson H (2020-03-11). "Mass testing, alerts and big fines: the strategies used in Asia to slow coronavirus". The Guardian.
  14. ↑ Adam D (April 2020). "Special report: The simulations driving the world's response to COVID-19". Nature. 580 (7803): 316–318. Bibcode:2020Natur.580..316A. doi:10.1038/d41586-020-01003-6. PMID 32242115. S2CID 214771531.
  15. ↑ Squazzoni F, Polhill JG, Edmonds B, Ahrweiler P, Antosz P, Scholz G, et al. (2020). "Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action". Journal of Artificial Societies and Social Simulation. 23 (2): 10. doi:10.18564/jasss.4298. ISSN 1460-7425. S2CID 216426533.
  16. ↑ Sridhar D, Majumder MS (April 2020). "Modelling the pandemic". BMJ. 369: m1567. doi:10.1136/bmj.m1567. PMID 32317328. S2CID 216074714.
  17. ↑ 17.0 17.1 Maziarz M, Zach M (October 2020). "Agent-based modelling for SARS-CoV-2 epidemic prediction and intervention assessment: A methodological appraisal". Journal of Evaluation in Clinical Practice. 26 (5): 1352–1360. doi:10.1111/jep.13459. PMC 7461315. PMID 32820573.
  18. ↑ Mayorga L, García Samartino C, Flores G, Masuelli S, Sánchez MV, Mayorga LS, Sánchez CG. "A modelling study highlights the power of detecting and isolating asymptomatic or very mildly affected individuals for COVID-19 epidemic management." BMC Public Health. 2020 Nov 27;20(1):1809. doi: 10.1186/s12889-020-09843-7. PMID: 33246432 Retrieved 14 January 2021.
  19. ↑ Maziarz M, Zach M (October 2020). "Agent-based modelling for SARS-CoV-2 epidemic prediction and intervention assessment: A methodological appraisal". Journal of Evaluation in Clinical Practice. 26 (5): 1352–1360. doi:10.1111/jep.13459. PMC 7461315. PMID 32820573.
  20. ↑ Andrew Atkeson, Karen Kopecky und Tao Zha: Four stylized facts about Covid-19. NBER Working Paper, August 2020, Introduction p. 2–4, Conclusion p. 15–16. Retrieved 2020-09-12.
  21. ↑ Empty citation (help) With link to the complete NBER Working Paper, August 2020, there Figure 2, p. 18.

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