The population of Zambia: past, present and future

doi:10.21203/rs.3.rs-1617840/v1

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The population of Zambia: past, present and future

https://doi.org/10.21203/rs.3.rs-1617840/v1

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Background

The population size, age structure, and the changes thereof have significant effects on a country’s social, economic and political dispensation. Understanding future fertility and mortality trends is key in forecasting future population patterns and levels; an outcome crucial for planning for the changing population age structure, economic and social needs as well as the geopolitical space. In this paper, we used fertility, mortality and migration forecasts from expert opinions to project the population of Zambia from the year 2015 to 2060 and consequently discuss what this may mean in terms of implications both for population programming and policy changes.

Methods

In order to project Zambia’s future population size, PADIS INT, a deterministic modelling tool capable of supporting multi-scenario and multi-group forecasts with extensive horizons was used. Projections were split into three variant-based scenarios, which included – a reference scenario also called medium, alternative scenarios (plunge and enhanced) – based on the rate of change of fertility, mortality and migration.

Results

The medium scenario projects the population growth rate at 2% per annum in 2060, a drop of about 0.8% percentage points from the 2015 growth rate. The medium variant shows further that the population will reach a high of 49.4 million people in 2060 representing a 2.1 times increase in population size from the base of 16.1 million people in 2015. Our findings also indicate a shifting age structure in the medium scenario from 3% to 6% of the population age 65 years and above. Overall dependency ratio will reduce from 92% to 61% while old age dependency will increase from 5.8% to 9.7% between 2015 and 2060. TFR would reduce from 4.8 in 2020 to 3.2 in 2060 and RNI from 29% to 20% during the same time interval. The medium scenario projects that a bit more people are likely to leave Zambia with a net migration of 62 persons per 100,000 population in 2020 and 43 persons per 100,000 population in 2060.

Conclusions

These results show that while the population will increase significantly for the period in question, fertility will continue to reduce; these results are consistent in both the reference and alternative scenarios. These results may be indicative of improvements in female education attainment, female participation in remunerable work, as well as better sexual and reproductive health and rights. Continued population growth has other several policy implications for the social, economic and political development of Zambia. Such population projections as conducted in this paper ideally supplement conventional data collection processes necessary for national development planning and policy space adjustment.

Population Projections

Fertility

Mortality

Age

Sex

Contemporary demographic trends consistently reveal that people live longer now than before. There exists a considerable lag between birth and the onset of childbearing, and age patterns by which these events are experienced is principally regular [1]. For example, in an early-peak type society, maximum births occurred in the age-group 20–24 years, and between 25–29 years in the late-peak type. In the broad-peak type, however, births in the two age groups differ only slightly and each largely exceed those of younger and older age groups respectively [2]. Since these fertility patterns transform rather slowly, populations (and their structure) can be predicted reliably over long horizons and still produce useful results. Demographers and forecasters have consistently defined concepts associated with numerical counts of the population at different points in time referred to as “estimates”, “projections” or “forecasts” [3]. Both estimates, which relate to past or present demographic information, and projections and forecasts, which refer to future population information [4], [5], are important tools utilized in procedures for computing structures of populations at later points in time. Granular level information of future populations stratified by age, sex, race and other characteristics play a crucial role at all levels of social and economic development planning [6], [7]. At the international level for instance, the United Nations (UN) and other specialized agencies use population projections to monitor developmental goals such as the Sustainable Development Goals (SDGs); and at regional and local levels, social scientists, health researchers as well as the private sector use population projections for strategic policy and marketing decisions, and to build paradigms [7]–[9].

Like many Sub-Saharan African countries, Zambia has a short history of gathering population data [10]. The first comprehensive census did not take place until 4-years after attaining political independence in 1969 [11]. The next census was conducted 11-years later in 1980 [11], [12] and since then, decennial censuses of population and housing have been conducted [11]–[14], until the COVID-19 pandemic, in large part, interrupted the undertaking of the sixth, which was due in 2020. In terms of projections, the first national and subnational population projections were based on the 2010 Census of Population and Housing [14] spanning the horizon 2011–2035 [15]. Results of these projections indicate that mortality and fertility will continue as primary determinants of the country’s present and future population size, distribution and structure. For example, births would increase by 18.7% between 2011 and 2020 (from 608,076 to 721,993) and by 54.9% between 2011 and 2035 (from 608,076 to 941,979). As for mortality, although it was set to decline during the projection period, absolute deaths increased from 185,694 in 2011 to 212,364 in 2020 and could potentially reach 234,627 by 2035 [15].

Notwithstanding the forgoing, accurate knowhow of future populations, their size and structure, provide a snapshot of target populations for an assortment of interventions even at the lowest administrative level. Population projection results allow for more accurate evaluations of the severity of public health threats and help in specifying indicators for monitoring progress in health planning and policy-relevant population-based initiatives. Zambia’s current projections do not span farther than 2035, but for the country to lay up medium to long term development plans, projections of population size beyond what is available are needed. This study aimed to project the national level population size and structure for the period 2015 to 2060 and discuss consequences and implications of these changes overtime.

Estimates of the 2015 population distribution and its ensuing age structure sourced from the United Nations’ World Population Prospects (WPP) were used to project the age-sex distribution of Zambia's population from 2015–2060 [16]. Demographic and socio-economic publications released by Zambia Statistical Agency (ZSA) were also considered to build methods for this study. Tables with various national and regional population data were retrieved from the statistical databank [17]. Based on historical census and demographic data, we projected the population of Zambia from 2015 to 2060 to measure medium to long term changes in various demographic indices. Projections were conducted using PADIS INT [18], a deterministic model developed by the China Population and Development Research Center (CPDRC) and Digital Health China with support from the United Nations Population Fund (UNFPA). Fertility, mortality and migration schedules necessary for developing projection variants or scenarios are based on expert opinions obtained from the Wittgenstein Centre Human Capital Data Explorer [19].

We modelled the future population of Zambia based on three alternative scenarios producing an indication of what the future population might look like under given varying levels of fertility, mortality and migration. This whole process comprised two main parts: The first part was designed to project the population of Zambia from 2015 to 2060 to obtain actual absolute growth estimates of the population, and the second part comprised of conducting systematic analyses of the population to explicate the consequences and implications of changes in Zambia’s future population.

Projections Assumptions

We investigated global dynamics in population change and overall nation-wide demographics of Zambia to derive our assumptions into the future. Population distributions are presented in 5-year periods starting from 2015 up until 2060. By size, Zambia’s population is relatively smaller compared with other populations in sub-Saharan Africa such that long term projections yield less accurate estimates. In order to formulate assumptions, data from censuses and demographic and health surveys conducted between 1969 to 2015 were utilized to calibrate recent shifts in demographic dynamics and patterns. We considered available complete data in projections to aid smoothing abrupt outliers while providing a continuation in presenting demographic trends.

Three scenarios, based on three projection components were explored to determine the future population of Zambia. Fertility, mortality and migration are the important factors in these projections and were presented by age and sex. Other projections based on specific population rates were made and they include: death rates, rates of reproduction, labor force, etc. to mention but a few. Table 1 presents assumptions about which population dynamics driving the future size and structure of Zambia’s population and perceived changes therein.

Description of the three scenarios

1. The 'Medium' scenario projects a continuation of current trends into the future; thus it is also considered the reference scenario. Changes in fertility, mortality and migration dictate the sway for the size and structure of the future population.

2. The 'Enhanced' scenario suggests a multi-level development approach for Zambia that directly or indirectly affects the future population size and structure. It is derived from the assumption of considerable reductions in mortality and fertility but also bulged negative net migration. Changes in weather conditions and technological advancement will make the country more favorable for new industrial set up, mineral and oil exploration as well as infrastructure development which may in turn constitute the main stimuli for immigration. We, however, foresee an increase in emigration due to improvements in education and exposure to a variety of opportunities offered by the world outside Zambia.

3. The 'Plunge' scenario entails static or increasing fertility and mortality with little or no migration. Here, population grows to much higher than the reference scenario due to inadequate access to contraception but also lack of development initiatives. It represents a stalled development agenda for the country.

Results in this study are presented in four ways: firstly, we present the past and present population levels, trends and drivers of change for the period 1969 to 2015; secondly, we focus our attention to show population dynamics responsible for future changes in population size and age structure; thirdly, we present future scenarios of population while also elaborating on growth rates in the reference and alternative scenarios from 2015 to 2060; and lastly, we discuss determinants and implication of the results especially for the period 2015 to 2060 emphasizing on 2030 with a view to align these results with Zambia’s Vision 2030 and the United Nations' sustainable development goals (SDGs) agenda.

Past and present

The population of Zambia stood at 4.1 million people in 1969 when the first census of population was conducted [20]. The growth rate leading to the 1969 population count was estimated at 2.5%, a TFR of 7.4 children per woman and life expectancy at birth of 47 years. Between 1969 and 1980, the population grew at 3.1% reaching 5.7 million [21]. The TFR reduced by 0.2 children from the 1969 rate and life expectancy at birth increased by 5 years. Table 2 shows population size and other key past and present population indicators.

Migration has traditionally contributed significantly minimally to changes in the population of Zambian. Except for the year 2000 when Zambia recorded 0.4% net migration, the reference point reported negative net migration. The highest net migration was in 1995 at -3.5% [22]. Dependency ratios were highest at 110 dependents per 100 persons aged 15-64 in 1980 and lowest in 2015 at 92%.

Mortality

The mortality picture shows that Life expectancy at birth is expected to rise for all scenarios. Overall, life expectancy for the reference scenario will increase from 63 years in 2020 to 68 years in 2060 in the medium scenario. The Enhanced scenario shows greater change over time and much more for females than for males. Table 3 displays expectations of life at birth by sex and by projection scenarios based on the trends in mortality. Life expectation at birth was highest in the enhanced scenario (63 year in 2015 and 75 years in 2060).

Migration

Migration insignificantly influences the size, structure and form of the Zambian population. We modelled migration such that a more realistic influence of migration can be measured and the extent to which it affects the future size of the population under alternative scenarios elaborated. Table 4 presents anticipated changes in net migration during the projection period based on scenario specifications presented in table 1. Our reference scenario migration figures were projected to peak at 16,000 emigrants in 2025 and gradually reduce to 9,250 in 2060.

Fertility

Figure 1 presents changes that would occur to Zambia’s population dynamics in terms of TFR. The TFR is expected to decline from about 5 children per woman in 2015 to 3.2 children in 2060 in the reference scenario while the enhanced scenario shows a drop to an average 1.6 children per woman in 2060. The reference and plunge alternative scenarios remain well above replacement level fertility at the projection horizon unlike enhanced.

Projected Population (Future)

We projected absolute population counts in the reference scenario (medium), plunge and enhanced. We also focused life expectancy, fertility, mortality and migration that are projected to increase but slower for the plunge scenario. Our reference scenario projections indicate that the population of Zambia will increase 2.1 times the initial population reaching 49.3million in 2060 from 16.1 million in 2015. During the same reference period, total population in the “Enhanced” scenario is forecasted to grow by 1.5 times to 29,427,022 in 2060. This change is represented by an annual average increase of 2.9% for the medium scenario compared with 3.3% and 2.4% for the plunge and enhanced scenarios respectively (figure 2).

Populations would increase at a much slower rate as we approach 2055 ((2.2% plunge, 0.7% enhanced compared with 2.1% medium) See figure 2)). The steady growth trajectory in the “Enhanced” scenarios owes to an optimistic assumption about the level of reduction in fertility and mortality but also emigration. Owing to the assumption of higher fertility than the medium and enhanced scenarios, plunge projection will yield a population 2.4 times that of the initial population - 54.9 million people in 2060. Notwithstanding, the population of Zambia is poised for growth at an average rate of at least 2% when observed from the medium scenario. Table 5 suggests that the population of Zambia will have doubled in the Plunge (by 2.4 times) and Medium (by 2.1 times) by 2060, while total population will slightly increase by 83% in the Enhanced scenario relative to baseline levels.

Table 5 summarizes the projection results for the rate of natural increase – an interplay of birth and death rates. Fertility promises to be higher than mortality for both reference and alternative scenarios. The medium scenario’s RNI is expected to reduce from a high of 29.3% in 2020 to a low of 19.7% in 2060.

The rate of natural increase (RNI) is expected to remain well above 10 in the high fertility plunge starting at 33% in 2020 to 17.4% in 2060. Compared with the medium scenario, the enhanced scenario shows a huge decline from 19.5% in 2020 to 3.9% natural increase in 2060 due mainly to higher than medium scenario survival and extremely low TFR

Projected age-sex distributions

Projections of Zambia’s age-sex distribution for the period 2015, 2020, 2030, 2040, 2050 and 2060 are illustrated in figures 2, 3 and 4. They provide an overview of changes occurring in the population age-sex structure under alternative scenarios. (For actual proportions see the appendix).

Figure 3 depicts the age-sex structure of the 16.1 million Zambians as estimated in 2015. Clearly, the distribution between males and females portrays no conspicuous variation signifying a stable sex ratio through the ages. Males tend to be more than females at birth generally due to a higher sex ratio at conception and at birth; but females, however, survive more thereby increasing their numbers in later years except during childbearing. The initial age structure reveals that 45% of Zambia’s population was age 0-14 while those aged 15-64 and 65+ constituted 52.1% and 2.5% respectively (see figure 3 and supplementary material).

If fertility continues increasing, the population would reach 26.2 million (18% percentage increase) by 2030 and 54.9 million in 2060 (2.4 times greater than initial population) if TFR of 3.24 birth per woman prevailed in 2060. This would result in a much younger age structure compared to the reference scenario as depicted in figures 4 to 6. The median age of the population would increase from 16 years in 2015 to 17.2 years in 2030 reaching a high of 22 years in 2060 under this scenario compared to moderately higher median ages in the medium projection – 18.9 years in 2030 and 24.9 years in 2060.

Although the TFR would have fallen from 5.5 in 2020 to 3.24 in 2060, absolute births would continue to outnumber deaths (RNI of 33.2% in 2030 and 17.8% in 2060) under the plunge scenario. There would be 832,111births and 147,076 deaths in 2030 and 1,261,167 births and 276,783 deaths (RNI = 28.2 in 2030 and 19.7 in 2060) in 2060 under the medium projection scenario. These changes in fertility and mortality conditions under this scenario would be influenced by moderate reductions in average childbearing age from 28.7 years in 2020 to 28.2 years in 2030 and eventually to 27.5 years in 2060 in the plunge scenario compared with minor reductions of 28.5 years in 2030 and 28.3 years in 2060 under the medium scenario.

The plunge scenario results in a slightly higher dependency ratio in 2060 – 64 per 100 compared with 62 per 100 in the medium projection scenario. Dependency ratios would remain relatively high however; decreasing from 91.9 per 100 in 2015 to 83 per 100 in 2030 under the plunge scenario compared with 72.2 per 100 under the medium scenario in the same year. Child dependency ratio would drop from 87% to 53% per 100 between 2015 and 2060 while old age dependency would increase from 4.8% to 8% during the same period in the plunge projection.

The medium projection assumes recent reductions in mortality over the projection period. The crude death rate (CDR) is projected to reduce from 7.5 per 1000 population in 2020 to 6.1 per 1000 in 2030 and 5.1 per 1000 in 2060. The infant mortality rate (IMR) and under five mortality rate (U5MR) are also projected to reduce under the medium projection from IMR of 62.8 per 1000 live births in 2020 to 34.6 per 1000 live births in 2060. Similarly, U5MR is projected to reduce from 113.5 per 1000 live births in 2020 to 47.7 in 2060. The reduction is associated with 11.8 years gains in life expectancy from 63.2 years in 2020 to 74 years in 2060. However, if male and female life expectancy at birth increased by 1.03 and 1.12 years each year, they could both reach 73 years and 77 years in 2060 (enhanced projection) respectively. In this scenario the population would reach 29.4 million in 2060. This is 19,920,544 less people than under the medium projection. The proportion of the population age 65 years and over would nearly quadruple from 2.5% in 2015 to 9.8% in 2060 raising the old age dependency from 4.8% in 2015 to 13.7% in 2060 in the enhanced scenario.

With more people in older ages, the population would age much faster than in the medium scenario – the median age of the population would be over 35.8 years in 2060. The general dependency ratio would be lower from 2020 all the way to 2060 compared with the medium projection. However, more people are posed to leave Zambia with net migration of 11,300 (62 persons per 100,000 population) compared with 11,500 (62 persons per 100,000 population) in 2020 and 47,000 (235 persons per 100,000 population) and 9,250 (43 persons per 100,000 population) for enhanced and medium scenarios respectively – all favoring emigration.

Summary of results

Based on our reference scenario (medium), the population of Zambia will continue to grow and reach 49.3 million people in 2060 from 16.1 million in 2015; increasing 2.1 times the base population. This increase is likely to be driven by growth rates to range between 2.9% for the period 2015-2020 and 1.96% for the 2055-2060 period. The highest growth in population size will be recorded in the plunge scenario (54.9 million people in 2060) expected to grow between 3.3% and 1.96% in 2015-2020 and 2055-2060 periods respectively. Our results also show that compared with the medium scenario, the enhanced projection will have the slowest growth of the population – reaching 29.4 million by 2060. The enhanced projection results show failure to double the population in over 4 decades with indicative percentage growth of 0.45% per year in 2055-2060 from 2.4% per year in the 2015-2020 period.

Main drivers of change in population size remain fertility, mortality and less migration. TFR will reduce for all scenarios from at least 5 children per woman in 2015 for all scenarios, to a low of 2 children per woman in 2060 for the medium scenario while the enhanced scenario show the lowest TFR of 1.5 children per woman. The crude death rate will range from 8.7 per 1000 population in 2020 to 9.2 per 1000 population in 2060 for plunge projection compared with a high rate of 7.5 per 1000 population in 2020 and a low of 5.1 per 1000 population in 2060 for the medium scenario. Lowest mortality was projected in the enhanced scenario – with a CDR of 6.3 per 1000 in 2020 and 6.1 deaths per 1000 population in 2060 respectively. The RNI is projected to high in 2020 at 28.2% and lowest in 2060 at 17.7% in the medium scenario while the plunge projection indicates a RNI of 33.2% and 17.8% for the same period, all mainly due to mortality reduction. The enhanced scenario posted highest gains in terms of fertility-mortality interplay with RNI of 19.5% in 2020, 15.7% in 2030 and 5.3% in 2060. This scenario is attainable due to its lower than replacement level fertility starting around 2040.

Population figures and proportions recorded under the plunge scenario have no migration influence hence being a product of fertility and mortality only since migration is assumed to be zero. The enhanced and medium scenarios show higher negative net migration at both projection launch and horizon. More people are posed to leave Zambia with net migration of 62 persons per 100,000 population compared with 62 persons per 100,000 population in 2020 and 235 persons per 100,000 population and 43 persons per 100,000 population in 2060 for enhanced and medium scenarios respectively – all favoring emigration.

Strengths and weakness of the deterministic method of projection

The major strength of the deterministic population projections is that it requires minimal data demands to estimate mortality, fertility and migration to project future population characteristics. Secondly, due to the fact that fertility, mortality and migration play a central role in the deterministic methodology, this is considered a strength since it allows users (mostly demographers) to draw on specialized knowledge of each of these components of population change to make reliable projections. However, this method has limitations as well; the fact that the method relies on conveying uncertainties based on variant scenarios (such as High and Low projections) using different assumptions about future vital rates has been criticized as lacking validity because it has no probabilistic basis and leads to possible contradictions. However, even with such perceived weaknesses, we used this method mainly because our data elements in Zambia, as it also obtains in other parts of the developing world are quite scanty and suffer from reliability challenges to the extent that the deterministic methods of population projections produce as good point estimates as other methods such as probabilistic methods even with basic data.

Consequences and implications of the future size, age and sex structure of the Zambian population

Population momentum is the inherent driving force for population growth which is a consequence of the existing age structure. A population with a higher percentage of young people (especially those below the ages of 15) will continue to grow as this cohort enters reproductive ages even where fertility reaches below replacement level. The balance between fertility and mortality and to a lesser extent migration create the necessary momentum for future growth. The immediate impact of high fertility (resulting from declining childhood mortality and high birth rate) is an increase in the number of children added to the general population and a reduction in the share of the population concentrated in the working ages, dipping the support ratio and correspondingly decreasing per capita income (Kelley and Schmidt 1999, 2005; Mason, Studies, and Lee 2004). The future of the population of Zambia, as observed from the three scenario results is expected to undergo varied changes based on fertility-mortality interplay. Changes in sex ratios at different ages and survival poses new challenges for the study of demography, healthcare, labor economics, reproduction, to mention but a few.

Economic consequences and implications

Shifts in population structure bears economic and fiscal consequences that sometimes prove challenging. Ceteris paribus, an increase in the labor force alone will increase GDP growth rates. According to Chang et al, productivity per working age adult will continue[23]; having fewer individuals between the ages of 15 and 64 years might, however, have larger effects on GDP growth[24]. Projected population growth observed in all three scenarios serves Zambia quite well since an increase in the working-age population not only increases GDP but also innovation in the economy since more persons in the workforce (15-64) may boost domestic markets due to a more likelihood of this group gravitating towards consumer durables than those aged 65 and above. Not only does this increase in the young adults and middle aged population increase GDP in this population group, it also raises the support ratio and balloons per capita income [25], [26]. This phenomenon is referred to as the first demographic dividend [25], [27]–[29]. Such shifts in the population age distribution have important macroeconomic consequences that feature prominently in discussions around economic outlooks for developing countries. As observed in these projections, the proportion of seniors is expected to keep growing beyond 2060 putting pressure on the population entering the working age thereby surging old age dependence rates. This change will have dire effects on the social welfare as well as the pension system if not well planned for.

The steady increase in the proportion of the aging population calls for substantial investments in old-age care through a functioning pension and social security system, housing, savings, labor supplies, social services, and in many other sectors[30] to protect future work force from the burden of caring for the old. This can reduce stress among the working population and stimulate savings. If the surviving elderly (as adult mortality declines) are supported by transfers, either from their adult children or from public sector pension supported by current tax revenues, then a higher total dependency ratio means greater burden on the working age population (Williamson and Higgins, 2001; Lee, Mason and Miller, 2000). Our results show that the working age population will grow from 52.1% in 2015 to 58.1% in 2030 and then 61.7% in 2060 in the medium scenario. The bulge in the working age population will be accompanied by growth in “older-age” population from a baseline value of 2.5% in 2015 to 6.2% in 2060 under the medium scenario. To the extent that the elderly contribute to their own support through saving and asset accumulation earlier in their lives and utilize in retirement, population aging may cause lower aggregate saving rates (Williamson and Higgins, 2001; Lee, Mason and Miller, 2000). Nonetheless, even with lower saving rates, the capital/labor ratio may rise since the labor force is still growing but only slowly (Cutler et al., 1990; Lee et al., 2000). This pattern of savings and wealth accumulation may arise through individual life cycle savings or institutional requirements. The net effect would then be to stimulate growth in labor productivity due to capital deepening (Lee, 2003).

Labor market participation

Economic growth advocates have insisted that current fertility schedules in developing countries are a major hindrance to achieving growth [25], [31]. Once fertility declines, net consumption will equally decline leading to enhanced saving and reinvestment in productive sectors of the economy. Similarly, interesting to note is the change in proportions of males and females. As the sex structure transforms through proportional contributions of each sex to the population, sex composition changes will induce social changes in terms of gender roles, female labor force participation, and independence of choice of mating partners[32]. This will also affect marriage patterns and consequently marital fertility. Changes in gender roles and mindset of the females and their guardians regarding the importance of female education will have far reaching outcomes on the education structure of the population. This will eventually advantage women as they will feature prominently in productive and remunerated work that is beneficial to themselves and the country. This will enhance the feminization of the workforce – the movement of women into occupations they were previously underrepresented[33]. Due to the shifting gender balance in labor force participation, women are expected to take up more roles in out-of-the-house productivity even if this will remain lower than that of men [34], [35]. Increased proportions of women in remunerable employment in the last decade can be linked to removal of regulations in the labor market, fragmented production process, changes in the industrial structure and export specialization [36]. In parts of the Caribbean, Central America, south and south-east Asia, light industry export-processing zones have employed labor which is overwhelmingly young and female [36]. Investments in education and health for girls, rural children and other underrepresented population groups contributes to having an educated, healthy and productive workforce.

Health and healthcare

The disease burden Zambia faces is immense due mainly to the high prevalence of communicable diseases and rapidly growing non- communicable diseases. Over the years, considerable progress has been made in most indicators such as life expectancy, maternal mortality, infant and child mortality etc. Despite the gains, statistics about these indicators remain unacceptably high such that there is urgent need to improve the delivery of health products to match with the national health targets and SDGs. Malnutrition also poses a significant threat to child health and survival with the prevalence of stunting in Zambia currently standing at 40% . Uneducated and poor mothers are more likely to have malnourished children posing a huge risk for the future of the country. Advancing education for women has ripple effects for the current and future generations in terms of health and economic achievements of the country. In terms of major health issues, Zambia has continued to record reductions in HIV prevalence among adults aged between 15 and 49 years, from 16% in 2002 to 11.1% in 2018 [37], [38]. However, the health sector has recorded remarkable progress regarding treatment of HIV through provision Antiretroviral Treatment (ART), currently standing at 72% of the eligible people against the UNAIDS global target of 90%. Zambia is one of the thirty high TB burden countries with a TB national prevalence of 638 cases per 100,000 in the adult population. The prevalence is generally higher among women (15.1%) compared to men (11.3%) [39]. Malaria remains endemic throughout the country with 336 cases per 1,000 population in 2015 [40]. Non-Communicable Diseases account for 22.6% of the total deaths in the country. This health backdrop requires strengthening the healthcare system by enduring availability, accessibility and affordability of health services. This eventually will provide a positive response to the structure and composition of the future population.

The population of Zambia will continue to grow with little possibility of levelling off by 2060. Even with declining fertility and reducing growth rates, the population momentum will continue to catapult the population growth beyond 2100. Since changes in the age structure of the population might be accompanied by changes in labor force participation, with more women participating than before, changes to education policies to upskill women are inevitable. This realization needs to be accompanied by investments in construction of new education and health institutions to cater for a growing population. The projected population growth will most likely culminate in larger overall GDP with diverse social and economic benefits. It suffices therefore to mention that these projections for Zambia are not cast in stone as a demographic certainty, however, shifting the trajectory for fertility, mortality and migration is dependent on policies that countries, especially developing ones such as Zambia practice now.

Acknowledgements

Not applicable.

Authors’ contributions

NM conceived the study, NM analyzed the data, NM, TNM, XQ and WJ interpreted the results. TNM, XQ and CCM reviewed the initial manuscript. All authors read and approved the final manuscript.

Funding

No funding

Availability of data and materials

Data used in performing this modeling are available from the United Nations (https://population.un.org/wpp/Download/Standard/Population/) and from the Wittgenstein Center for Demography and Human Capital (http://dataexplorer.wittgensteincentre.org/wcde-v2/)

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Author details

₁ Institute of Population Research, Peking University, No. 5 Yiheyuan Road, Beijing, China, 100871. ₂Department of Population Studies, University of Zambia, Great East Road Campus, Lusaka, Zambia 10101. ₃ Global Strategy Lab, Faculty of Health, York University, 4700 Keele Street, Toronto, Canada. ₄ The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249-1644. ₅ School of Demography and Population Studies, University of Witwatersrand, Johannesburg, South Africa. ₆ Optentia research Unit, North-West University, South Africa.

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Table 1: Scenarios and population dynamics assumptions for projections

	Medium (Reference) Scenario 1	Plunge Scenario 2	Enhanced Scenario 3
Fertility	TFR is expected to continue to decline based on current levels as observed in the most recent data available in Zambia. This is due to a general but gradual decrease in the PASFR which drive TFRs. PASFR are highest among women in 25-29 but the proportions increase overtime while those in the younger age groups reduce. Based on this scenario TFR is expected to decline slowly from 4.8 in 2015 to 3.08 in 2060. The scenario is pessimistic as it assumes a TFR of 4.25 in 2030.	TFR is expected to continue to decline from baseline levels of 4.8 in 2015 to 5.21 in 2030. In terms of PASFR, most births will be occurring to women age 20-24 followed by 25-29. All ages will see a decline in PASFR over the projection period. A further gradual decline in TFR is expected to reach 3.8 children in 2060.	TFR is forecasted to continue with a downward trend, reaching 2.39 by 2030, replacement fertility by 2040 (TFR=2.01) and further to below replacement (1.56) in 2060. The highest proportions for PASFR will among women age 25-29 followed by 20-24 up until 2025 when the PASFR will be second highest in the age group 30-34 signifying a shift timing of births.
Mortality	Based on historical schedule of ASDR by sex and utilizing survival ratios constructed using the Relational Brass Logit Mortality Model by age and sex, LE by sex was extracted from the same life table that was expected to steadily rise from 59.6 year among males and 65.0 for females in 2015 to 72 and 76 years for males and females respectively in 2060. This scenario assumes gradual decline in infectious diseases as well as a minimal rise in NCDs.	Mortality is assumed to reduce at a slower rate than medium resulting in LE of 58.9 and 63.9 years for males and females respectively 2060 signifying a decline 0.7 years decline for males and 1.1 years during the projection period. This scenario assumes minimal reduction in infectious diseases as the main cause of death and a slight rise in NCDs.	Mortality rates by age and sex are expected to reduce at much faster than the medium scenario thereby increasing the average survival ratio as well as LE. LE for males and females would increase by 13 years and 12.3 years reaching 72.6 years and 76.8 years respectively in 2020.
Migration	Baseline migration level towards equilibrium in 2025 so that the country’s immigration and emigration probabilities converge to their average; net migration reaches zero from 2030 to 2060	Baseline migration level towards equilibrium in 2025 so that the country’s immigration and emigration probabilities converge to their average; net migration reaches zero from 2030 to 2060.	In-migration increases by 10% during each 5-year period until 2030, after that the growth in number of incomers is set at 5% reaching 4 times that of baseline year by 2060

Table 2: Selected indicators for Populations between 1969 and 2015

Period	Population	LE₀	TFR	Growth rate	Dependency Rate	Net migration[22]
1969[21]	4,056,995	47.0	7.4	2.5
1980[21]	5,661,801	52.0	7.2	3.1	110
1990[23]	7,383,097	47.0	6.7	2.7	95.1	-2.0%
2000[24]	9,885,591	50.0	6	2.4	96.2	0.4%
2010[14]	13,092,666	51.2	5.9	2.8	92.5	-2.7%
2015[25]	16,100,579	62.3	5.3	2.8	91.9	-0.7%

Table 3: Life Expectancy at birth by sex and projection scenario

	Medium			Plunge			Enhanced
Period	Male	Female	All	Male	Female	All	Male	Female	All
1969			47.0
1980	51.6	53.1	52.0
1990	46.1	47.6	47.0
2000	48.0	52.0	50.0
2010	49.0	52.0	51.2
2015	59.6	65.0	62.3	59.6	65.0	62.3	59.6	65.0	62.3
2020	60.3	65.7	63.0	59.1	64.5	61.8	61.8	67.1	64.5
2025	61.0	66.3	63.7	59.1	64.5	61.8	63.4	68.5	66.0
2030	61.7	67.0	64.4	59.2	64.5	61.9	64.9	69.9	67.4
2035	62.4	67.6	65.0	59.2	64.4	61.8	66.4	71.1	68.8
2040	63.1	68.2	65.7	59.1	64.3	61.7	67.7	72.3	70.0
2045	63.9	68.9	66.4	59.1	64.2	61.7	69.0	73.5	71.3
2050	64.6	69.5	67.1	59.0	64.1	61.6	70.2	74.6	72.4
2055	65.3	70.1	67.7	59.0	64.0	61.5	71.4	75.7	73.6
2060	66.0	70.8	68.4	58.9	63.9	61.4	72.6	76.8	74.7

Table 4: Absolute net migration by sex and scenario

Year	Enhanced			Medium			Plunge
	Male	Female	Total	Male	Female	Total	Male	Female	Total
2015	-	-	-	-	-	-	-	-	-
2020	-7500	-3800	-11300	-5750	-5750	-11500	-2800	-1500	-4300
2025	-10100	-6300	-16400	-8000	-8000	-16000	0	0	0
2030	-12500	-8600	-21100	-6500	-6500	-13000	0	0	0
2035	-15000	-11000	-26000	-5000	-5000	-10000	0	0	0
2040	-17600	-13500	-31100	-5000	-5000	-10000	0	0	0
2045	-20000	-16000	-36000	-5000	-5000	-10000	0	0	0
2050	-22200	-18200	-40400	-5000	-5000	-10000	0	0	0
2055	-24000	-20000	-44000	-4875	-4875	-9750	0	0	0
2060	-25400	-21600	-47000	-4625	-4625	-9250	0	0	0

Table 5: Population Projection and change relative to baseline

Year	Plunge	Proportionate Change	Medium	Proportionate Change	Enhanced	Proportionate Change
2015	16,100,579	-	16,100,579	-	16,100,579	-
2020	18,930,061	0.18	18,569,366	0.15	18,148,087	0.13
2025	22,318,201	0.39	21,407,458	0.33	19,979,163	0.24
2030	26,242,387	0.63	24,616,792	0.53	21,691,775	0.35
2035	30,533,344	0.90	28,166,009	0.75	23,386,859	0.45
2040	35,051,398	1.18	31,969,835	0.99	25,057,319	0.57
2045	39,787,603	1.47	35,965,390	1.23	26,588,586	0.65
2050	44,740,940	1.78	40,189,398	1.50	27,838,388	0.73
2055	49,831,105	2.10	44,662,504	1.77	28,772,932	0.79
2060	54,908,777	2.41	49,347,566	2.07	29,427,022	0.83

Table 6: Projected Rates of Natural Increase for Zambia

Year	Plunge Scenario	Medium Scenario	Enhanced Scenario
2015	-	-
2020	33.04	29.31	19.53
2025	32.98	29.09	16.81
2030	31.2	28.21	15.71
2035	28.32	26.8	15.05
2040	25.5	24.9	13.95
2045	23.42	23.23	11.76
2050	21.69	22.01	9.22
2055	19.76	20.9	6.99
2060	17.8	19.66	5.3
2065	17.42	18.34	3.85

No competing interests reported.

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The population of Zambia: past, present and future

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