Analysis Presentation
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Country analysis Is it is possible today? Ana Maria Henao- Restrepo Initiative for Vaccine Research ‘Scientific’ and decision-support modelling Scientific Decision-driven Starting point What can we find out about X? What should be done about X? eg values of transmission parameters eg should we change the EPI schedule? Tasks Fit model/predict/learn/revise + explore policy options and scenarios Inputs Scientific evidence Scientific evidence Assumptions/hypotheses + estimates, preferences/values, consensus, attitudes to risk Output Understanding of causal chains + pros and cons of options for different outcomes Inconsistencies in the data Robustness of choices to scenarios/preferences Plausibility of hypotheses Important gaps in knowledge Important gaps in knowledge • In DS modelling, uncertainty may arise not just from imprecision of observable data, but from the effects of events yet to come, including decisions by other ‘players’. • Exploring the implications of different scenarios or ‘futures’ is thus an important part of it. Prototype DS model for exploring alternative schedules Excel: familiar interface users can examine formulae and trace cause-effect links relatively simple to develop and amend Graphics: users can ‘see’ the data used, and the impact of scenarios on intermediate variables eg coverage Simplified: model outcome is not lives or cases prevented; it is cases in a pre-vaccine cohort who would have had 1, 2, 3 and 4 doses of vaccine under a given schedule. Ie any assumptions about vaccine effectiveness or herd immunity are outside the model. 2 3 4 5 14/12/2016 15:59 Setup Country Bangladesh BGD Diseases Pertussis Hib SP IPD Rotavirus Impact on Severe cases Year 2020 Schedules decision support model_v6.xlsm 5 Pert Hib IPD Rota 2 3 Data Numbers of cases aged < 5y at risk from GDB studies Age distribution by disease, from the literature Age-specific vaccine coverage: most recent survey Protection: duration Results Age distributions: Severe cases Severe cases estimated in unvaccinated populations Bangladesh DHS6: age-specific population duration in years Bangladesh: coverage of cases, doses/child by age Pert coverage 5 250,000 Burden SEAR3.50% 120% 1st dose 2.0% Hib 5 Population 5 2nd dose No doses 205,196 3.00% 1.8% IPD coverage 5 197,733 197,733Pert 197,733193,134 100% 3rd dose 200,000 1st dose Hib 197,733 Rota Booster 5 1.6% 2.50% 2nd dose IPD 205,196 80% 1.4% 3rd dose 150,000 Rota 193,134 1.2% 2.00% Booster #N/A 60% DTP1 1.0% #N/A 1.50% 100,000 0.8% DTP2 ageof % week cases per of frequency density 40% 0.6% 1.00% DTP3 50,000 0.4% 0.50% 20% MCV 0.2% #N/A #N/A 0.0% 0 0.00% 0% 0 52 104 156 Pert Hib IPD Rota 0 50 100 150 0 52 104 156 Age in weeks age in weeks age in weeks Scenario Age distributions and adjustments Use this scenario as baseline in SA Clears current Current schedule Proposed schedule % of 'expected' cases not covered given target coverage include target final(36m) timeliness 0% 20% 40% 60% 80% 100% Default Adjusted Add this scenario to trial set for SA with age at 36m this dose? age (wks) coverage of coverage dose 1 1st dose DTP1 (wks)6 97.3% yes 6 as DTP1 as DTP1 1 1 dose 2 dose 3 10 94.9% Pert Age specific incidence by disease 2nd dose DTP2 yes 10 as DTP2 as DTP2 2 2 boost Pert location? 0.0% 500.0 1.578 1.578 2 3rd dose DTP3 14 92.0% yes 14 as DTP3 as DTP3 3 3 3.5% Pert dose 1 shape? 0.0% 500 79.09 79.09 Booster MCV1 38 88.8% yes 39 as MCV as MCV 4 4 dose 2 Hib dose 3 500 Hib 3.0% IPD boost Hib location? 0.0% 500.0 5.00 5.00 3 Age-specific coverage with chosen schedule Rota dose 1 shape? 0.0% 500.0 6.00 6.00 100% dose 2 2.5% dose 3 500 IPD boost IPD location? 0.0% 500.0 1.56 1.56 4 2.0% Pert 80% dose 1 shape? 0.0% 500.0 37.18 37.18 coverage dose 2 Hib dose 3 500 Rota IPD 60% boost Rota location? 0.0% 500.0 4.35 4.35 1.5% 5 Rota dose 1 shape? 0.0% 500.0 11.03 11.03 1st dose 2 40% 500 No data 1.0% dose dose 3 boost location? 0.0% 500.0 #N/A #N/A #N/A 2nd dose dose 1 shape? 0.0% 500.0 #N/A #N/A 0.5% 20% 3rd dose 2 500 No data dose 3 dose boost location? 0.0% 500.0 #N/A #N/A 0.0%#N/A 0% shape? 0.0% 500.0 #N/A #N/A - 50.0 100.0 150.0 0 52 104 156 age in weeks old new 2 3 4 5 14/12/2016 15:59 Setup Country Bangladesh BGD Diseases Pertussis Hib SP IPD Rotavirus Impact on Severe cases Year 2020 Schedules decision support model_v6.xlsm 5 Pert Hib IPD Rota 2 3 Data Numbers of cases aged < 5y at risk from GDB studies Age distribution by disease, from the literature Age-specific vaccine coverage: most recent survey Protection: duration Results Age distributions: Severe cases Severe cases estimated in unvaccinated populations Bangladesh DHS6: age-specific population duration in years Bangladesh: coverage of cases, doses/child by age Pert coverage 5 250,000 Burden SEAR3.50% 120% 1st dose 2.0% Hib 5 Population 5 2nd dose No doses 205,196 3.00% 1.8% IPD coverage 5 197,733 197,733Pert 197,733193,134 100% 3rd dose 200,000 1st dose Hib 197,733 Rota Booster 5 1.6% 2.50% 2nd dose IPD 205,196 80% 1.4% 3rd dose 150,000 Rota 193,134 1.2% 2.00% Booster #N/A 60% DTP1 1.0% #N/A 1.50% 100,000 0.8% DTP2 ageof % week cases per of frequency density 40% 0.6% 1.00% DTP3 50,000 0.4% 0.50% 20% MCV 0.2% #N/A #N/A 0.0% 0 0.00% 0% 0 52 104 156 Pert Hib IPD Rota 0 50 100 150 0 52 104 156 Age in weeks age in weeks age in weeks Scenario Age distributions and adjustments Use this scenario as baseline in SA Clears current Current schedule Proposed schedule % of 'expected' cases not covered given target coverage include target final(36m) timeliness 0% 20% 40% 60% 80% 100% Default Adjusted Add this scenario to trial set for SA with age at 36m this dose? age (wks) coverage of coverage dose 1 1st dose DTP1 (wks)6 97.3% yes 6 as DTP1 as DTP1 1 1 dose 2 dose 3 10 94.9% Pert Age specific incidence by disease 2nd dose DTP2 yes 10 as DTP2 as DTP2 2 2 boost Pert location? 0.0% 500.0 1.578 1.578 2 3rd dose DTP3 14 92.0% yes 14 as DTP3 as DTP3 3 3 3.5% Pert dose 1 shape? 0.0% 500 79.09 79.09 Booster MCV1 38 88.8% yes 39 as MCV as MCV 4 4 dose 2 Hib dose 3 500 Hib 3.0% IPD boost Hib location? 0.0% 500.0 5.00 5.00 3 Age-specific coverage with chosen schedule Rota dose 1 shape? 0.0% 500.0 6.00 6.00 100% dose 2 2.5% dose 3 500 IPD boost IPD location? 0.0% 500.0 1.56 1.56 4 2.0% Pert 80% dose 1 shape? 0.0% 500.0 37.18 37.18 coverage dose 2 Hib dose 3 500 Rota IPD 60% boost Rota location? 0.0% 500.0 4.35 4.35 1.5% 5 Rota dose 1 shape? 0.0% 500.0 11.03 11.03 1st dose 2 40% 500 No data 1.0% dose dose 3 boost location? 0.0% 500.0 #N/A #N/A #N/A 2nd dose dose 1 shape? 0.0% 500.0 #N/A #N/A 0.5% 20% 3rd dose 2 500 No data dose 3 dose boost location? 0.0% 500.0 #N/A #N/A 0.0%#N/A 0% shape? 0.0% 500.0 #N/A #N/A - 50.0 100.0 150.0 0 52 104 156 age in weeks old new 2 3 4 5 14/12/2016 15:59 Setup Country Bangladesh BGD Diseases Pertussis Hib SP IPD Rotavirus Impact on Severe cases Year 2020 Schedules decision support model_v6.xlsm 5 Pert Hib IPD Rota 2 3 Data Numbers of cases aged < 5y at risk from GDB studies Age distribution by disease, from the literature Age-specific vaccine coverage: most recent survey Protection: duration Results Age distributions: Severe cases Severe cases estimated in unvaccinated populations Bangladesh DHS6: age-specific population duration in years Bangladesh: coverage of cases, doses/child by age Pert coverage 5 250,000 Burden SEAR3.50% 120% 1st dose 2.0% Hib 5 Population 5 2nd dose No doses 205,196 3.00% 1.8% IPD coverage 5 197,733 197,733Pert 197,733193,134 100% 3rd dose 200,000 1st dose Hib 197,733 Rota Booster 5 1.6% 2.50% 2nd dose IPD 205,196 80% 1.4% 3rd dose 150,000 Rota 193,134 1.2% 2.00% Booster #N/A 60% DTP1 1.0% #N/A 1.50% 100,000 0.8% DTP2 ageof % week cases per of frequency density 40% 0.6% 1.00% DTP3 50,000 0.4% 0.50% 20% MCV 0.2% #N/A #N/A 0.0% 0 0.00% 0% 0 52 104 156 Pert Hib IPD Rota 0 50 100 150 0 52 104 156 Age in weeks age in weeks age in weeks Scenario Age distributions and adjustments Use this scenario as baseline in SA Clears current Current schedule Proposed schedule % of 'expected' cases not covered given target coverage include target final(36m) timeliness 0% 20% 40% 60% 80% 100% Default Adjusted Add this scenario to trial set for SA with age at 36m this dose? age (wks) coverage of coverage dose 1 1st dose DTP1 (wks)6 97.3% yes 6 as DTP1 as DTP1 1 1 dose 2 dose 3 10 94.9% Pert Age specific incidence by disease 2nd dose DTP2 yes 10 as DTP2 as DTP2 2 2 boost Pert location? 0.0% 500.0 1.578 1.578 2 3rd dose DTP3 14 92.0% yes 14 as DTP3 as DTP3 3 3 3.5% Pert dose 1 shape? 0.0% 500 79.09 79.09 Booster MCV1 38 88.8% yes 39 as MCV as MCV 4 4 dose 2 Hib dose 3 500 Hib 3.0% IPD boost Hib location? 0.0% 500.0 5.00 5.00 3 Age-specific coverage with chosen schedule Rota dose 1 shape? 0.0% 500.0 6.00 6.00 100% dose 2 2.5% dose 3 500 IPD boost IPD location? 0.0% 500.0 1.56 1.56 4 2.0% Pert 80% dose 1 shape? 0.0% 500.0 37.18 37.18 coverage dose 2 Hib dose 3 500 Rota IPD 60% boost Rota location? 0.0% 500.0 4.35 4.35 1.5% 5 Rota dose 1 shape? 0.0% 500.0 11.03 11.03 1st dose 2 40% 500 No data 1.0% dose dose 3 boost location? 0.0% 500.0 #N/A #N/A #N/A 2nd dose dose 1 shape? 0.0% 500.0 #N/A #N/A 0.5% 20% 3rd dose 2 500 No data dose 3 dose boost location? 0.0% 500.0 #N/A #N/A 0.0%#N/A 0% shape? 0.0% 500.0 #N/A #N/A - 50.0 100.0 150.0 0 52 104 156 age in weeks old new 2 3 4 5 14/12/2016 15:59 Setup Country Bangladesh BGD Diseases Pertussis Hib SP IPD Rotavirus Impact on Severe cases Year 2020 Schedules decision support model_v6.xlsm 5 Pert Hib IPD Rota 2 3 Data Numbers of cases aged < 5y at risk from GDB studies Age distribution by