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vaxCEA2.m
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function vaxCEA2()
%% load results
paramDir = [pwd , '\Params\'];
load([paramDir, 'general'])
noV = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0_Eff_0.7.mat']);
c60_2vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.6_Eff_0.7.mat']);
c60_9vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.6_Eff_0.9.mat']);
c30_9vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.3_Eff_0.9.mat']);
c30_2vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.3_Eff_0.7.mat']);
c90_9vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.9_Eff_0.9.mat']);
c90_2vFull = load([pwd , '\HHCoM_Results\Vaccine\CEA_VaxCover_0.9_Eff_0.7.mat']);
% noV = load('H:\HHCoM_Results\VaxCover_0_Eff_0.9.mat');
% c90_2vFull = load('H:\HHCoM_Results\VaxCover_0.9_Eff_0.7.mat');
% c70_2vFull = load('H:\HHCoM_Results\VaxCover_0.7_Eff_0.7.mat');
% c70_9vFull = load('H:\HHCoM_Results\VaxCover_0.7_Eff_0.9.mat');
% c70_2vPartial = load('H:\HHCoM_Results\VaxCover_0.7_Eff_0.63.mat');
% c90_9vFull = load('H:\HHCoM_Results\VaxCover_0.9_Eff_0.9.mat');
% c90_2vPartial = load('H:\HHCoM_Results\VaxCover_0.9_Eff_0.63.mat');
tVec = c60_2vFull.tVec;
annlz = @(x) sum(reshape(x , stepsPerYear , size(x , 1) / stepsPerYear));
annAvg = @(x) sum(reshape(x , stepsPerYear , size(x , 1) / stepsPerYear)) ./ stepsPerYear;
% midMat = zeros(stepsPerYear , size(o90.popVec , 1) / stepsPerYear);
% midMat(1 , :) = 1;
% midMat(end , :) = 1;
% midAnn = @(x) sum(midMat .* reshape(x , stepsPerYear , size(x , 1) / stepsPerYear)) / 2;
c = fix(clock);
currYear = c(1); % get the current year
%%
reset(0)
set(0 , 'defaultlinelinewidth' , 2)
%% Calculate life years saved
% If y = current year, count benefits and CC treatment costs for women aged
% >= y - B, where B = last year eligible for inclusion
% Since 5 year age groups are being used, at ea ch year y, count benefits
% for women in age group (round((y-B)/5)) and above.
basePopTot = zeros(length(tVec) , 1);
c60_2vFull.ly = zeros(length(tVec) , 1);
c60_9vFull.ly = c60_2vFull.ly;
c30_9vFull.ly = c60_2vFull.ly;
c30_2vFull.ly = c60_2vFull.ly;
c90_9vFull.ly = c60_2vFull.ly;
c90_2vFull.ly = c60_2vFull.ly;
c90_2vFull.ccCosts = zeros(length(tVec) , 1);
c90_9vFull.ccCosts = c90_2vFull.ccCosts;
yrIntStart = 2018;
% CC Costs
ccCost = [2617 , 8533 ,8570]; % local, regional, distant
for i = 1 : length(tVec)
a = min(max(round((tVec(i) - yrIntStart) / 5) , 1) , age);
ageCounted = toInd(allcomb(1 : disease , 1 : viral , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , 2 , a : age , 1 : risk));
% No intervention case
basePopTot(i) = sum(noV.popVec(i , ageCounted) , 2);
% Intervention cases
c60_2vFull.ly(i) = sum(c60_2vFull.popVec(i , ageCounted) , 2);
c60_9vFull.ly(i) = sum(c60_9vFull.popVec(i , ageCounted) , 2);
c30_9vFull.ly(i) = sum(c30_9vFull.popVec(i , ageCounted) , 2);
c30_2vFull.ly(i) = sum(c30_2vFull.popVec(i , ageCounted) , 2);
c90_9vFull.ly(i) = sum(c90_9vFull.popVec(i , ageCounted) , 2);
c90_2vFull.ly(i) = sum(c90_2vFull.popVec(i , ageCounted) , 2);
% Cervical cancer costs
c90_2vFull.ccCosts = sum(sum(sum(c90_2vFull.ccTreated(: , : , : , a : age , 1) , 2) , 3) , 4) .* ccCost(1) + ...
sum(sum(sum(c90_2vFull.ccTreated(: , : , : , a : age , 2) , 2) , 3) , 4) .* ccCost(2) + ...
sum(sum(sum(c90_2vFull.ccTreated(: , : , : , a : age , 3) , 2) , 3) , 4) .* ccCost(3);
c90_9vFull.ccCosts = sum(sum(sum(c90_9vFull.ccTreated(: , : , : , a : age , 1) , 2) , 3) , 4) .* ccCost(1) + ...
sum(sum(sum(c90_9vFull.ccTreated(: , : , : , a : age , 2) , 2) , 3) , 4) .* ccCost(2) + ...
sum(sum(sum(c90_9vFull.ccTreated(: , : , : , a : age , 3) , 2) , 3) , 4) .* ccCost(3);
end
c60_2vFull.lys = c60_2vFull.ly - basePopTot;
c60_9vFull.lys = c60_9vFull.ly - basePopTot;
c30_9vFull.lys = c30_9vFull.ly - basePopTot;
c30_2vFull.lys = c30_2vFull.ly - basePopTot;
c90_9vFull.lys = c90_9vFull.ly - basePopTot;
c90_2vFull.lys = c90_2vFull.ly - basePopTot;
%% Calculate annual costs
% HIV Costs
hospCost = [117 , 56 , 38 , 38]; % <200 , 200-350, >350 , on ART
artCost = 260;
% CC Costs
ccCost = [2617 , 8533 ,8570]; % local, regional, distant
% HIV Indices
above350Inds = toInd(allcomb(4 , 1 : viral , 1 : hpvTypes , 1 : hpvStates , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
cd200_350Inds = toInd(allcomb(5 , 1 : viral , 1 : hpvTypes , 1 : hpvStates , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
under200Inds = toInd(allcomb(6 , 1 : viral , 1 : hpvTypes , 1 : hpvStates , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
artInds = toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : hpvStates , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
% CC Indices
localInds = toInd(allcomb(1 : disease , 1 : viral , 2 : hpvTypes , 5 , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
regionalInds = toInd(allcomb(1 : disease , 1 : viral , 2 : hpvTypes , 6 , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
distantInds = toInd(allcomb(1 : disease , 1 : viral , 2 : hpvTypes , 7 , 1 : periods , ...
1 : gender , 1 : age , 1 : risk));
% HIV costs
c90_2vFull.hivCosts = sum(c90_2vFull.popVec(: , above350Inds) , 2) .* hospCost(1) + ...
sum(c90_2vFull.popVec(: , cd200_350Inds) , 2) .* hospCost(2) + ...
sum(c90_2vFull.popVec(: , under200Inds) , 2) .* hospCost(3) + ...
sum(c90_2vFull.popVec(: , artInds) , 2) .* (hospCost(4) + artCost);
c90_9vFull.hivCosts = sum(c90_9vFull.popVec(: , above350Inds) , 2) .* hospCost(1) + ...
sum(c90_9vFull.popVec(: , cd200_350Inds) , 2) .* hospCost(2) + ...
sum(c90_9vFull.popVec(: , under200Inds) , 2) .* hospCost(3) + ...
sum(c90_9vFull.popVec(: , artInds) , 2) .* (hospCost(4) + artCost);
% CC Costs
% c90_2vFull.ccCosts = sum(sum(sum(c90_2vFull.ccTreated(: , : , : , : , 1) , 2) , 3) , 4) .* ccCost(1) + ...
% sum(sum(sum(c90_2vFull.ccTreated(: , : , : , : , 2) , 2) , 3) , 4) .* ccCost(2) + ...
% sum(sum(sum(c90_2vFull.ccTreated(: , : , : , : , 3) , 2) , 3) , 4) .* ccCost(3);
%
% c90_9vFull.ccCosts = sum(sum(sum(c90_9vFull.ccTreated(: , : , : , : , 1) , 2) , 3) , 4) .* ccCost(1) + ...
% sum(sum(sum(c90_9vFull.ccTreated(: , : , : , : , 2) , 2) , 3) , 4) .* ccCost(2) + ...
% sum(sum(sum(c90_9vFull.ccTreated(: , : , : , : , 3) , 2) , 3) , 4) .* ccCost(3);
% Vaccination
cost2v = 27; % cost of 2 doses of bivalent vaccine
c90_2vFull.vaxCost = annlz(c90_2vFull.vaxd) * cost2v;
% c70_2vFull.vaxCost = c70_2vFull.vaxd;
% c70_9vFull.vaxCost = sc70_9vFull.vaxd;
% c70_2vPartial.vaxCost = c70_2vPartial.vaxd;
% c90_9vFull.vaxCost = c90_9vFull.vaxd;
% c90_2vPartial.vaxCost = c90_2vPartial.vaxd;
% NPV of vaccination cost
discountRate = 0.03; % discount rate of 3% per annum
c90_2vFull.vaxCostNPV = pvvar(c90_2vFull.vaxCost , discountRate);
%% Find price threshold
% ceThreshold = 1540; % USD per LYS
% priceGuess = 100;
% ce9v = @(x) abs(pvvar(annlz(c90_9vFull.vaxd) * x - annlz(c90_2vFull.vaxd) .* cost2v ...
% + annAvg((c90_9vFull.hivCosts + c90_9vFull.ccCosts)) - annAvg((c90_2vFull.hivCosts + c90_2vFull.ccCosts)) , discountRate) ...
% / pvvar(annAvg(c90_9vFull.lys) - annAvg(c90_2vFull.lys) , discountRate) - ceThreshold);
% priceThreshold_9v = fminsearch(ce9v , priceGuess);
% disp(['With a cost-effectiveness threshold of ' , num2str(ceThreshold) , ' USD, ' ,...
% 'the unit cost of 9v vaccine must be less than or equal to ' , ...
% num2str(round(priceThreshold_9v , 2)),' USD.'])
%% CC only price threshold
% 3 thresholds: 0.5x GDP , 1x GDP , 500 USD per LYS
ceThreshold = 1540; % USD per LYS
ceThresholds = [0.5 * ceThreshold , ceThreshold , 500];
for i = 1 : length(ceThresholds)
priceGuess = 100; % Enter a price guess for 9v to seed the search process
% ce9v is an anonymous function that finds the vaccine price that
% places the 9v vaccine right at the cost-effectiveness threshold
% specified by ceThresholds(i)
ce9v = @(x) abs(pvvar(annlz(c90_9vFull.vaxd) * x - annlz(c90_2vFull.vaxd) .* cost2v ...
+ annlz((c90_9vFull.ccCosts)) - annlz((c90_2vFull.ccCosts)) , discountRate) ...
/ pvvar(annlz(c90_9vFull.lys) - annlz(c90_2vFull.lys) , discountRate) - ceThresholds(i));
priceThreshold_9v = fminsearch(ce9v , priceGuess);
disp(['9v vs 2v: Considering only CC costs, with a cost-effectiveness threshold of ' , num2str(ceThresholds(i)) , ' USD, ' ,...
'the unit cost of 9v vaccine must be less than or equal to ' , ...
num2str(round(priceThreshold_9v , 2)),' USD.'])
end
% 3 thresholds: 0.5x GDP , 1x GDP , 500 USD per LYS
ceThreshold = 1540; % USD per LYS
ceThresholds = [0.5 * ceThreshold , ceThreshold , 500];
for i = 1 : length(ceThresholds)
priceGuess = 27; % Enter a price guess for 2v to seed the search process
% ce9v is an anonymous function that finds the vaccine price that
% places the 9v vaccine right at the cost-effectiveness threshold
% specified by ceThresholds(i)
ce9v = @(x) abs(pvvar(annlz(c90_2vFull.vaxd) * x ...
+ annlz((c90_2vFull.ccCosts)) - annlz((noV.ccCosts)) , discountRate) ...
/ pvvar(annlz(c90_2vFull.lys) , discountRate) - ceThresholds(i));
priceThreshold_9v = fminsearch(ce9v , priceGuess);
disp(['2v vs No Vaccine: Considering only CC costs, with a cost-effectiveness threshold of ' , num2str(ceThresholds(i)) , ' USD, ' ,...
'the unit cost of 9v vaccine must be less than or equal to ' , ...
num2str(round(priceThreshold_9v , 2)),' USD.'])
end
%% YLS
figure()
plot(tVec(1 : stepsPerYear : end) , annAvg(c90_9vFull.lys) - annAvg(c90_2vFull.lys))
title('Years of Life Saved'); xlabel('Year'); ylabel('Years of life Saved')
figure()
plot(tVec(1 : stepsPerYear : end) , annlz(c90_9vFull.vaxd))
title('Vaccinated with 9v'); xlabel('Year'); ylabel('Number vaccinated')
%% CC incidence reduction
inds = {':' , [2 : 6 , 10] , [2 : 6] , 1 , 10};
files = {'CEA CC_General_Hpv_VaxCover' , 'CEA CC_HivAll_Hpv_VaxCover' , ...
'CEA CC_HivNoART_Hpv_VaxCover' , 'CEA CC_HivNeg_Hpv_VaxCover' ,...
'CEA CC_ART_HPV_VaxCover'};
plotTits = {'General' , 'HIV-Positive' , 'HIV-Positive (No ART)' , ....
'HIV-Negative' , 'HIV-Positive on ART'};
fac = 10 ^ 5;
noV_Hpv = zeros(1 , length(tVec) / stepsPerYear);
% c70_2vPartial_Inc = noV_Hpv;
% c90_9vFullInc = noV_HpvAge;
% c90_2vFullInc = noV_HpvAge;
% v90_2vFullInc = noV_HpvAge;
for i = 1 : length(inds)
% general
allF = [toInd(allcomb(1 : disease , 1 : viral , 1 : hpvTypes , 1 : 4 , ...
1 : periods , 2 , 4 : age , 1 : risk)); ...
toInd(allcomb(1 : disease , 1 : viral , 1 : hpvTypes , 9 : 10 , ...
1 : periods , 2 , 4 : age , 1 : risk))];
% All HIV-positive women
allHivF = [toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 1 : 4 , ...
1 : periods , 2 , 4 : age , 1 : risk)); ...
toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 9 : 10 , ...
1 : periods , 2 , 4 : age , 1 : risk));...
toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : 4 , ...
1 : periods , 2 , 4 : age , 1 : risk)); ...
toInd(allcomb(10 , 6 , 1 : hpvTypes , 9 : 10 , ...
1 : periods , 2 , 4 : age , 1 : risk))];
% HIV-positive women not on ART
hivNoARTF = [toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 1 : 4 , ...
1 : periods , 2 , 4 : age , 1 : risk)); ...
toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 9 : 10 , ...
1 : periods , 2 , 4 : age , 1 : risk))];
% All HIV-negative women
hivNeg = [toInd(allcomb(1 , 1 : viral , 1 : hpvTypes , 1 : 4 , 1 : periods , ...
2 , 4 : age , 1 : risk)); ...
toInd(allcomb(1 , 1 : viral , 1 : hpvTypes , 9 : 10 , 1 : periods , ...
2 , 4 : age , 1 : risk))];
% Women on ART
artF = [toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : 4 , ...
1 : periods , 2 , 4 : age , 1 : risk)); ...
toInd(allcomb(10 , 6 , 1 : hpvTypes , 9 : 10 , ...
1 : periods , 2 , 4 : age , 1 : risk))];
genArray = {allF , allHivF , hivNoARTF , hivNeg , artF};
noV_Hpv = ...
annlz(sum(sum(sum(noV.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(noV.popVec(: , genArray{i}) , 2) ./ stepsPerYear))* fac;
c30_2vFullInc = ...
annlz(sum(sum(sum(c30_2vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c30_2vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
c60_2vFullInc = ...
annlz(sum(sum(sum(c60_2vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c60_2vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
c90_2vFullInc = ...
annlz(sum(sum(sum(c90_2vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c90_2vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
c30_9vFullInc = ...
annlz(sum(sum(sum(c30_9vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c30_9vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
c60_9vFullInc = ...
annlz(sum(sum(sum(c60_9vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c60_9vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
c90_9vFullInc = ...
annlz(sum(sum(sum(c90_9vFull.newCC(: , inds{i} , : , 4 : age),2),3),4)) ./ ...
(annlz(sum(c90_9vFull.popVec(: , genArray{i}) , 2) ./ stepsPerYear)) * fac;
figure()
plot(tVec(1 : stepsPerYear : end) , noV_Hpv , ...
tVec(1 : stepsPerYear : end) , c30_2vFullInc , ...
tVec(1 : stepsPerYear : end) , c60_2vFullInc , ...
tVec(1 : stepsPerYear : end) , c90_2vFullInc , ...
tVec(1 : stepsPerYear : end) , c30_9vFullInc , ...
tVec(1 : stepsPerYear : end) , c60_9vFullInc , ...
tVec(1 : stepsPerYear : end) , c90_9vFullInc)
title([plotTits{i} , ' Cervical Cancer Incidence'])
xlabel('Year'); ylabel('Incidence per 100,000')
legend('No vaccination' , '30% Coverage (Full 2v)' , ...
'60% coverage (Full 2v)' , '90% coverage (Full 2v)' , ...
'30% Coverage (Full 9v)' , '60% coverage (Full 9v)' , ...
'90% coverage (Full 9v)')
% Reduction
c30_2vFull_Red = (c30_2vFullInc - noV_Hpv) ./ noV_Hpv * 100;
c60_2vFull_Red = (c60_2vFullInc - noV_Hpv) ./ noV_Hpv * 100;
c90_2vFull_Red = (c90_2vFullInc - noV_Hpv) ./ noV_Hpv * 100;
c30_9vFull_Red = (c30_9vFullInc - noV_Hpv) ./ noV_Hpv * 100;
c60_9vFull_Red = (c60_9vFullInc - noV_Hpv) ./ noV_Hpv * 100;
c90_9vFull_Red = (c90_9vFullInc - noV_Hpv) ./ noV_Hpv * 100;
figure()
plot(tVec(1 : stepsPerYear : end) , c30_2vFull_Red , ...
tVec(1 : stepsPerYear : end) , c60_2vFull_Red , ...
tVec(1 : stepsPerYear : end) , c90_2vFull_Red , ...
tVec(1 : stepsPerYear : end) , c30_9vFull_Red , ...
tVec(1 : stepsPerYear : end) , c60_9vFull_Red , ...
tVec(1 : stepsPerYear : end) , c90_9vFull_Red)
title([plotTits{i} , ' Cervical Cancer Incidence Reduction'])
xlabel('Year'); ylabel('Reduction (%)')
legend('30% Coverage (Full 2v)' , '60% coverage (Full 2v)' , ...
'90% coverage (Full 2v)' , '30% Coverage (Full 9v)' , ...
'60% coverage (Full 9v)' , '90% coverage (Full 9v)')
axis([tVec(2) tVec(end) -100 0])
%
% T = table(tVec(1 : stepsPerYear : end)' , c30_2vFull_Inc' , ...
% c90_9vFullInc' , c60_2vFullInc' , ...
% c90_2vFull_Red' , c60_9vFull_Red' , c70_2vPartial_Red');
% writetable(T , [files{i} , '.csv'] , 'Delimiter' , ',')
end
%%
figure()
for g = 1 : 2
artInds = toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk));
artPop = sum(noV.popVec(: , artInds) , 2);
hivInds = toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 1 : hpvStates, ...
1 : periods , g , 4 : 10 , 1 : risk));
hivPop = sum(noV.popVec(: , hivInds) , 2);
plot(tVec , 100 * artPop ./ (hivPop + artPop))
hold on
end
xlabel('Year')
ylabel('Proportion of HIV Population')
title('Proportion on ART')
legend('Model (Male)' , 'Model (Female)')
%%
figure()
for g = 1 : 2
artInds = toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk));
artPop = sum(noV.popVec(: , artInds) , 2);
hivInds = toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 1 : hpvStates, ...
1 : periods , g , 4 : 10 , 1 : risk));
allInds = toInd(allcomb(1 : disease , 1 : viral , 1 : hpvTypes , 1 : hpvStates, ...
1 : periods , g , 4 : 10 , 1 : risk));
hivPop = sum(noV.popVec(: , hivInds) , 2);
allPop = sum(noV.popVec(: , allInds) , 2);
plot(tVec , 100 * (hivPop + artPop) ./ allPop)
hold on
end
xlabel('Year')
ylabel('Prevalence')
title('HIV Prevalence')
%%
hold on
for g = 1 : 2
artInds = toInd(allcomb(10 , 6 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk));
artPop = sum(c90_2vFull.popVec(: , artInds) , 2);
hivInds = toInd(allcomb(2 : 6 , 1 : viral , 1 : hpvTypes , 1 : hpvStates, ...
1 : periods , g , 4 : 10 , 1 : risk));
allInds = toInd(allcomb(1 : disease , 1 : viral , 1 : hpvTypes , 1 : hpvStates, ...
1 : periods , g , 4 : 10 , 1 : risk));
hivPop = sum(c90_2vFull.popVec(: , hivInds) , 2);
allPop = sum(c90_2vFull.popVec(: , allInds) , 2);
plot(tVec , 100 * (hivPop + artPop) ./ allPop)
hold on
end
legend('Male' , 'Female' , 'Male Vax' , 'Female Vax')
%%
figure()
for g = 1 : 2
hivSusInds = [toInd(allcomb(1 , 1 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk)); ...
toInd(allcomb(7 : 9 , 1 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk))];
hivSus = annlz(sum(c90_2vFull.popVec(: , hivSusInds) , 2)) ./ stepsPerYear;
plot(tVec(1 : stepsPerYear : end) , ...
annlz(sum(sum(c90_2vFull.newHiv(: , g , 4 : 10 , :) ...
, 3) , 4)) ./ hivSus * 100)
hold on
end
xlabel('Year'); ylabel('Rate Per 100'); title('HIV Incidence')
hold on
for g = 1 : 2
hivSusInds = [toInd(allcomb(1 , 1 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk)); ...
toInd(allcomb(7 : 9 , 1 , 1 : hpvTypes , 1 : hpvStates , ...
1 : periods , g , 4 : 10 , 1 : risk))];
hivSusNo = annlz(sum(noV.popVec(: , hivSusInds) , 2)) ./ stepsPerYear;
plot(tVec(1 : stepsPerYear : end) , ...
annlz(sum(sum(noV.newHiv(: , g , 4 : 10 , :) ...
, 3) , 4)) ./ hivSusNo * 100 )
end
legend('Male' , 'Female' , 'Male No Vax' , 'Female No vax')