What has been controversial and hotly debated since the project was commissioned are the costs of the road (see here, for example). The claim being made by many commentators is that the cost of constructing the road is many magnitudes higher than the cost in the region. There's been some allusion to the fact that South African roads, for example, cost a mere fraction of what the Lusaka-Ndola road will cost. Similar arguments have been made using examples from Namibia and Botswana.
The challenge in making comparisons about the unit costs of roads is that not any two roads are the same. Building a road between Johannesburg and Cape Town is not quite like building a road between Johannesburg and Durban and might even be vastly different from building a road between Lusaka and Ndola. Many factors drive cost differentials between what would otherwise be two identical roads. Some of the more obvious factors include geography (ruggedness of the terrain, rainfall, etc...) and proximity to markets for construction inputs (skilled labour, unskilled labour, materials, equipment, etc...). For example, a road project might be vastly advantaged by the fact that it's being built in a generally flat terrain with non-threatening rainfall. But the same project might be greatly disadvantaged by the fact that the market for important inputs is located thousands of kilometers away. A second project might face the exact opposite conditions to the first road (bad geography but close markets). A third road might have advantages in both factors (good geography, close markets). The implication of this is that comparing the costs of these three road projects would be meaningless.
What we need to do to meaningfully make comparisons is to compare like with like. That is, we need to compare mangoes with mangoes as opposed to comparing mangoes with masuku. One way of doing this is to search for two different road projects facing the EXACT same conditions (same rainfall, same terrain, same distance to markets, etc...) and make the cost comparison. But by definition, no two roads are exactly the same. This approach can be further complicated by other less obvious drivers of cost differentials like corruption or conflict.
We can get closer to a mangoes-to-mangoes type of comparison by collecting cost data on many road projects in many different countries overtime. We can then calculate summary cost statistics (average, median, mode, etc...) from the data and then use these statistics to make a statement about whether a road project under consideration is overpriced or not.
Using data from thousands of observations as opposed to only a few observations allows us to "average away" some of the idiosyncrasies associated with individual projects and this way gets us as close as we can to a mangoes-to-mangoes comparison. For example, your estimate of the average Zambian height would be closer to the truth if you obtained the average by measuring thousands of Zambians as opposed to only getting that average from only two Zambians. Your two Zambians might both be tall or both short or one short and the other tall. These idiosyncratic differences might mess up your estimate of the average. Having thousands of Zambians in your sample helps to average away these individual differences and therefore gets you closer to the true average height of the population.
To this end, the World Bank maintains a road cost database that it calls the Road Costs Knowledge System (ROCKS). ROCKS was started in 2001 with the aim of establishing an "international knowledge system of road costs -- to be used primarily in developing countries -- to establish an institutional memory, and obtain average and range unit costs based on historical data that could ultimately improve the reliability of new cost estimates and reduce the risks generated by cost overruns" (as quoted in Collier et al. 2015). To date, ROCKS has collected information on 3,222 road projects in 99 low and middle income countries (Zambia has 31 entries in the database, see Table S.1 of this paper). The extensive details about data collection and other detailed information about the database, including what constitutes road costs, can be accessed here and here.
Table S.2 below is an excerpt from Collier et al. (2015) who've analysed the data in the ROCKS database. The table shows the cost per km of constructing different types of roads (6 Lane highways, 4 Lane Highways and so on). The costs are expressed in 2000 US dollars to allow for comparison across time and across countries. The different summary measures presented are the mean (average), median (p50), standard deviation(sd), minimum (min) and maximum (max).
The table shows that the most expensive road type to construct is a New 6 Lane Expressway (it costs about US$5million per km in 2000 dollars). This is followed by a NEW 4L Expressway, followed by a NEW 4L Highway and so on.
So how does the cost of the Lusaka-Ndola Dual Carriageway fare in comparison to other similar projects across the world?
We know that the total cost of this project has been estimated at US$1.2billion (see here and here). The length of the road will be about 321 kilometers (see here). This works out to about US$3.7million per kilometer.
But before we can pass any judgement, we first have to convert the US$3.7million, which is in 2017 US dollars, into 2000 US dollars because Collier et al.'s data is expressed in 2000 dollars (this is technically known as deflating a nominal quantity into a real quantity).
After deflating, the unit cost of the Lusaka-Ndola Dual Carriageway, expressed in 2000 US dollars, is about US$2.6 million per kilometer . This cost estimate is not vastly different to the estimates provided by Collier et al for a NEW 4L Highway or a NEW 4L Expressway in Table S.2. In other words, the cost for the Lusaka-Ndola Dual Carriageway is inline with costs seen elsewhere. This conclusion is arrived at by comparing the cost of the road to costs derived from a large database of similar projects maintained by the World Bank.
An important caveat, however, contained in Collier et al's analysis is that road costs in low and middle income countries (which makeup the ROCKS database) are often inflated as a result of corruption. They find that "countries with corruption levels as measured by the Worldwide Governance Indicators above the median...have about 15% higher costs".
So if you think that Zambia is a generally corrupt place and if you believe Collier et al's analysis, then the road should cost about US$1.04billion instead of US$1.2billion .
 You can easily deflate nominal US dollars to real US dollars by using this online calculator which uses Consumer Price Index data from the US Bureau of Labour Statistics.
 I am generally sceptical of index measures of corruption in especially so-called poor places. See my previous writing on this here.
 Inflating US$1.04billion by 15% takes you to US$1.2billion.