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10.1016/j.vaccine.2015.04.022 http://scihub22266oqcxt.onion/10.1016/j.vaccine.2015.04.022 C4623312!4623312 !25900134     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=25900134 &cmd=llinks): Failed to open stream: HTTP request failed! 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The Benin experience: How computational modeling can assist major vaccine policy changes in low and middle income countries |pdf=|usr=}}{{25900134 }} gab.com Text The Benin experience: How computational modeling can assist major vaccine policy changes in low and middle income countries JO: Vaccine http://www.kidney.de/pget.php?&tw=1&pmid=25900134 #FOAvip While scientific studies can show the need for vaccine policy or operations changes, translating scientific findings to action is a complex process that needs to be executed appropriately for change to occur. Our Benin experience provided key steps and lessons learned to help computational modeling inform and lead to major policy change. The key steps are: engagement of Ministry of Health, identifying in-country "champions," directed and efficient data collection, defining a finite set of realistic scenarios, making the study methodology transparent, presenting the results in a clear manner, and facilitating decision-making and advocacy. Generating scientific evidence is one component of policy change. Enabling change requires orchestration of a coordinated set of steps that heavily involve key stakeholders, earn their confidence, and provide them with relevant information. Our Benin EVM+CCEM+HERMES Process led to a decision to enact major changes and could serve as a template for similar approaches in other countries. Twit Text FOAVip The Benin experience: How computational modeling can assist major vaccine policy changes in low and middle income countries ????Vaccine http://www.kidney.de/pget.php?&tw=1&pmid=25900134 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25900134 #FOAvip English Wikipedia <ref>{{Cite pmid|25900134 }}</ref> The Benin experience: How computational modeling can assist major vaccine policy changes in low and middle income countries #MMPMID25900134 Lee BY ; Schreiber B ; Wateska AR ; Connor DL ; Dicko HM ; Jaillard P ; Mvundura M ; Levin C ; Avella M ; Haidari LA ; Brown ST Vaccine 2015[Jun]; 33 (25 ): 2858-61 PMID25900134 show ga While scientific studies can show the need for vaccine policy or operations changes, translating scientific findings to action is a complex process that needs to be executed appropriately for change to occur. Our Benin experience provided key steps and lessons learned to help computational modeling inform and lead to major policy change. The key steps are: engagement of Ministry of Health, identifying in-country "champions," directed and efficient data collection, defining a finite set of realistic scenarios, making the study methodology transparent, presenting the results in a clear manner, and facilitating decision-making and advocacy. Generating scientific evidence is one component of policy change. Enabling change requires orchestration of a coordinated set of steps that heavily involve key stakeholders, earn their confidence, and provide them with relevant information. Our Benin EVM+CCEM+HERMES Process led to a decision to enact major changes and could serve as a template for similar approaches in other countries. |*Developing Countries [MESH] |*Health Policy/legislation & jurisprudence/trends [MESH] |*Immunization Programs [MESH] |*Policy Making [MESH] |*Vaccines [MESH] |Benin [MESH] |Humans [MESH]The Benin experience: How computational modeling can assist major vacc(epmc).pdf DeepDyve Pubget Overpricing