against-malaria-foundation-functional.squiggle

valueOfInterventionInPopulation(num_beneficiaries, population_age_distribution, benefitForPersonOfAge) = {
  age_of_beneficiaries = sampleN(population_age_distribution, num_beneficiaries)
  benefits_array = List.map(age_of_beneficiaries, {|a| benefitForPersonOfAge(a)})
  total_benefits = List.reduce(benefits_array, 0, {|acc, value| acc + value})
  total_benefits
}

valueWithUncertaintyAboutNumBeneficiaries(num_beneficiaries_dist, population_age_distribution, benefitForPersonOfAge) = {
  referenceN = 1000
  referenceValue = valueOfInterventionInPopulation(referenceN, population_age_distribution, benefitForPersonOfAge)

  numSamples = 1001
  num_beneficiaries_samples_list = sampleN(num_beneficiaries_dist, numSamples)
  benefits_list = List.map(num_beneficiaries_samples_list, {|n| referenceValue*n/referenceN})
  result = mixture(benefits_list)
  result
}

valueWithUncertaintyAboutPopulationShape(num_beneficiaries_dist, population_age_distribution_list, benefitForPersonOfAge) = {
  benefits_list = List.map(population_age_distribution_list, {|population_age_distribution| valueWithUncertaintyAboutNumBeneficiaries(num_beneficiaries_dist, population_age_distribution, benefitForPersonOfAge)})
  result = mixture(benefits_list)
  result
}

population_age_distribution_list = [to(1, 30),to(1, 40),to(1, 60), to(2, 30), to(2, 40), to(2, 60), to(3, 30), to(3, 40), to(3, 60), to(4, 50)]
num_beneficiaries_dist = 700  to 1500
life_expectancy = 40 to 60
benefitForPersonOfAge(age) = {
  result = age > 5 ? mx(0) : {
    counterfactual_child_mortality = SampleSet.fromDist(0.01 to 0.07)
    // https://apps.who.int/gho/data/view.searo.61200?lang=en
    child_mortality_after_intervention = counterfactual_child_mortality/2
    chance_live_before = (1-(counterfactual_child_mortality))^(5-age)
    chance_live_after =   (1-(child_mortality_after_intervention))^(5-age)
    value = (chance_live_after - chance_live_before) * (life_expectancy - age)
    value
  }
  result
}
valueWithUncertaintyAboutPopulationShape(num_beneficiaries_dist, population_age_distribution_list, benefitForPersonOfAge)