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Report from Group 2

Report from Group 2. Diseases of importance. HIV of course TB and malaria – need more modeling Drug resistance a major concern with both XDR TB: effectiveness of quarantine Regional differences Diseases important in context of HIV HSV2 and HPV. Key challenges for modeling in Africa.

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Report from Group 2

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  1. Report from Group 2

  2. Diseases of importance • HIV of course • TB and malaria – need more modeling • Drug resistance a major concern with both • XDR TB: effectiveness of quarantine • Regional differences • Diseases important in context of HIV • HSV2 and HPV

  3. Key challenges for modeling in Africa • extensive co-morbidities, • limited transportation • Scooters in Zambia • malnutrition, • prevalence of military and social conflict, • lack of education, • water systems, • climate, • and culture and traditions

  4. A broader scope • Modelers can contribute by widening their focus beyond disease transmission dynamics, to encompass public health practice and delivery. • model public health processes, such as data collection procedures, • help predict the impact of intervention programs. • help establish systems for monitoring and evaluation of public health programs, • assessing performance of laboratory tests or proxy models for laboratory tests.

  5. A broader scope (2) • operationalization of interventions • for instance, a model of vaccine impact in Africa might also consider cultural resistance to vaccine rollout; problems in transportation of vaccine to rural areas; cost issues; and behavioral disinhibition. • Related: • trading off better coverage with less optimal treatments, compared with using optimal treatments in less extensive populations

  6. Africa is not a country • Local data is important. • Local social networks and population structures are important to modeling • Local data changes rapidly, and so constant communication is necessary to create useful models and policy.

  7. Local perspectives are essential • When modeling is informed by local data and perspectives, the credibility of the model results will be higher with local policy makers. • Credibility is key to having recommendations accepted quickly • More likely to produce practical and applicable results, on a shorter time scale. • We can help our own credibility as modelers by making it explicit when we are modeling as an academic exercise, and when we’re modeling to answer applied and practical public health questions.

  8. Distributed problems • Require distributed solutions • Modeling as a part of the standard toolkit

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