# Prevention and control of non-communicable diseases in iran: the case for Investment – BMC Public Health

Jun 24, 2022

Investment cases include an economic component that assesses four main areas, including the economic burden incurred by countries due to NCDs, the costs of interventions to control them (selected from a set of interventions designated as “best buys” by the World Health Assembly), the impacts of these interventions in decreasing the burden of NCDs, and the cost–benefit analysis of these interventions for the countries in question (return on investment)[15, 16].

A multidisciplinary team comprised of staff from the authors institutes, the United Nations Interagency Task Force on the Prevention and Control of Non-communicable Diseases, and local experts from Iranian universities conducted different phases of the study, including data gathering, intervention selection, analysis, and manuscript preparation. Clinical interventions for cardiovascular diseases and diabetes were included in our analysis, along with policy interventions targeted at tobacco, salt consumption, and physical inactivity. A complete list of interventions is provided in Table 1. Of this list, interventions were finally chosen for the Return on Investment analysis (ROI) based on the availability of relevant data for computation of both costs and health impacts. The baseline year for our analysis was 2018.

The ROI analysis included four steps:

1. 1.

Economic burden analysis

2. 2.

Calculation of costs of clinical and policy interventions

3. 3.

Assessment of the health impacts and economic benefits of the interventions

4. 4.

Return on Investment analysis for 5- and 15-year time horizons

### Economic burden analysis

To calculate NCDs’ economic burden, we used the Cost-of-Illness analysis approach to approximate the direct, and indirect costs attributable to each of the selected NCDs, including cardiovascular diseases (CVDs), diabetes, cancer, and chronic respiratory disease. The direct costs included the value of all medical care expenditures, including diagnosis, treatment, and rehabilitation costs. Indirect costs included the costs associated with the decreases in the productivity or availability of the country’s workforce, including the costs of absenteeism, presenteeism, and mortality costs.

#### Total Direct costs

The total direct costs of NCDs were estimated via a top-down method that used the countrys National Health Accounts (NHAs). These costs included all the public and private expenditures related to NCD spending.

#### Total indirect costs

The indirect costs were computed in four steps as follows:

1. 1.

The annual value in terms of economic output was computed for each full-time worker in Iran based on the Gross Domestic Product (GDP) per employed person.

2. 2.

2.Data on the extent to which NCDs reduce labor productivity in the economy were incorporated into the calculation from the available literature on the reduction in labor force participation rate resulting from hypertension and diabetes, the reduction in full-time hours worked owing to absenteeism, and the reduction in productivity on account of presenteeism [17].

3. 3.

The exact number of employed people with NCDs in Iran was determined using the data on the labor force participation rate, unemployment rate, and mortality rates.

4. 4.

Finally, the economic losses from premature deaths were computed based on the number of active workers who had died and would be workers who could not participate in the labor market due to NCDs. Additionally, the costs associated with absenteeism and presenteeism for surviving active workers with NCDs were ascertained. The model applied the relevant productivity figures estimated in step 2 to the relevant population determined in step 3. Thus, the figure was multiplied with the Iranian GDP per employed person to arrive at the total indirect costs associated with each NCD group.

### Calculation of costs of clinical and policy interventions

We adopted a vertical program costing approach for costing of NCDs prevention program throughout the country. Two types of costs included in this approach the ingredient based costing at delivering level and the program costing at central level were estimated for clinical interventions. Since some of the activities associated with policy level interventions carried out outside of the health sector, the cost of these policies were estimated separately.

### Clinical interventions costing

#### Ingredient based costing

We used an ingredient based method to estimate the costs of interventions at delivery level. The costs of those interventions were calculated using the OneHealth Tool (OHT), which uses built-in functionality to estimate each intervention’s costs by computing the additional number of people in need of care targeted by the respective intervention multiplied by the per capita ingredient requirements for the intervention. This is finally multiplied with each ingredient unit cost to arrive at the total costs per intervention.

#### Program costing

Indeed, the program costing is seeking to quantify the value of those activities that are used at the central level for supporting the NCD program. These are activities related to training, information, supervision, evaluation, communication, administration and general program management. The OHT uses an activity-based costing (ABC) method to estimate the program costs.

### Policy level interventions

Policy level interventions are not delivered via health system, and then the costing method used for clinical interventions is not applicable. Instead, cost components of policy interventions are estimated in the same way for the program costing, ABC. The costs associated with the policy interventions were estimated with the WHO Costing Tool for NCD Prevention and Control. The tool costs human resources, training, external meetings, mass-media campaigns and other miscellaneous equipment needed to enact policies and programs based on assumptions made by the WHO experts on the magnitude of inputs required to implement and enforce each policy at the national, regional and district levels. more information about the methodology on WHO costing available from WHO CHOICE database[18].

The annual costs for both the policy and the clinical interventions were computed for a 15-year period. To compute the costs of both policy and clinical interventions, both tools require the baseline and target coverage levels for all interventions under study. The coverage levels (baseline and target) were obtained from different surveys (STEPS, IraPEN) and deliberations with experts[19].

### Assessment of the health impacts and economic benefits of the interventions

#### Health impacts

Health impacts are estimated through three effect measures of avoided incidence, avoided mortality and Healthy Life Years (HLYs) gained. The effect sizes for these measure were generated using the most valid and reliable evidence and have been built into the OHT tool. Estimating the health impacts in the OHT involves projecting forward two scenarios – the first one in which the current implementation continues as is, and another in which interventions are scaled up as per the coverage rates. The difference between the two scenarios provides us with incremental health impacts. The avoided incidences are modeled as result of policy and clinical interventions. The model employs the following formula to estimate the incidence of diseases in the population of interest.

$${mathrm{I}=left(1-mathrm{Cov}left({mathrm{t}}_{1}right)right)*mathrm{P}*{mathrm{E}}_{0}*{mathrm{R}}^{ab}+mathrm{Cov}left({mathrm{t}}_{1}right)*mathrm{P}*mathrm{E}}_{0}*{mathrm{R}}^{ab-d}$$

where, I is the incidence of a given disease, Cov (t1) is the coverage of the intervention for those who have a given risk factor, at time “1”, P is the prevalence of those with a given risk factor, ({E}_{0}) is the baseline prevalence of a disease event, R is the relative risk of a disease event for those who have a given level of a risk factor, starting from a baseline level for the risk factor, ab is the average number of units above a baseline level for the risk factor, d is the number of units of recovery towards a baseline level for the risk factor for those exposed to the intervention. Then, the change in incidence of event with increased coverage of the intervention is:

$$Delta mathrm{I}=mathrm{P}*Delta mathrm{Cov}*{mathrm{E}}_{0}*{mathrm{R}}^{mathrm{ab}}*1-{mathrm{R}}^{-mathrm{d}}$$

d is the effect of the intervention, which removes a certain percentage of the increased risk of event for those with risk factor as result of intervention. The avoided mortality and HLYs gained were measured based on the defined Markov health states for each disease’s pathway that were built into the OHT tool. The model uses real value of the transition probabilities to move among health states which have been extracted from the robust context specific evidence and fed into the model. In order to calculated the HLYs the disability weights associated with each state were also integrated into the model. These weights were also based on the most robust available evidence that WHO experts have incorporated into the model.

#### Economic benefits

To estimate the economic benefits of the interventions, the expected health benefits—avoided incidence, deaths, and healthy life years gained, are translated into economic gains through modeling the value of increased labor productivity (reduced indirect cost) derived from improved health, and avoided direct treatment costs. Many of the issues surrounding the monetization of indirect, and direct costs, as mentioned above, also apply to monetizing health impacts. Estimates for the net gain in worker productivity were obtained from the literature and fed into the model[15, 16].

### Return on Investment analysis

ROI was defined as the ratio of the discounted (present) value of the benefits to the costs of the health interventions. A model developed by WHO as part of the WHO/UNDP Joint Programme on Governance for NCDs in the year 2015 was used for our analysis. The tool helped us arrive at the estimates for economic gains expected to accrue from investing in both clinical and policy interventions using outputs generated by the OHT and the NCD costing tool as described above[20].

The ROI for each intervention package was arrived at by comparing the impact in terms of gains in GDP of the intervention package with the total costs of setting up and implementing the interventions using the net present value approach to future costs and economic gains with 5.8% discounting.

### Sensitivity analysis

We used a probabilistic approach to analyze the uncertainties regarding our ROI analysis results. Bootstraps of size 1000 each were created for the total costs and benefits of each intervention package. Then, we calculated ROIs for each row in each bootstrap and reported the medians, 2.5th and 97.5th percentiles for the resultant ROIs. Total costs and benefits were calculated by element-wise summation of the costs and benefits across all intervention group bootstraps. Then, 1000 ROIs were calculated using these sums for each of 5- and 15-year periods and the medians, 2.5th, and 97.5.th percentiles for the resultant ROIs were reported. To build our bootstraps, we used gamma distributions with shape parameters (κ > 0) and scale parameters (θ > 0) calculated using the following equations

$$upkappa =frac{overline{mathrm{x}}}{uptheta }$$

$$uptheta =frac{{mathrm{s}}^{2}}{overline{mathrm{x}} }$$

where the sample mean,(overline{mathrm{x} }), and the sample standard deviation, s.