Statistical Journal of the IAOS

Adoption of development agendas at different levels – national, regional, continental, and global level – has led to an unprecedented increase in demand for official statistics. This increase has not only brought to the fore a litany of challenges facing National Statistical Systems (NSSs) in Africa but also it has created opportunities for strengthening statistical production and development. This paper underscores the need for countries to take full advantage of these opportunities and increase investments in statistics, undertake data innovation, and expand and diversify data ecosystems, leveraging on the foundations of the data revolution for sustainable development and in line with current international statistical frameworks. The paper posits that these improvements will not happen coincidentally nor through ad hoc, piecemeal and uncoordinated approaches. Rather they will happen through more systematic, coordinated and multi-sectoral approaches to statistical development. The National Strategy for the Development of Statistics (NSDS) is presented as a comprehensive and robust framework for building statistical capacity and turning around NSSs in African countries. The paper unpacks the NSDS; elaborates the NSDS processes including; mainstreaming sectors into the NSDS, the stages of the NSDS lifecycle and the role of leadership in the NSDS proces; highlights NSDS extension; presents the design and implementation challenges, and the key lessons learned from the NSDS processes in Africa in the last 15 years or so.

By developing a methodology to measure citizens’ perceptions of governance, peace, and security, AFRISTAT has provided authorities at various levels with a policymaking tool. The governance, peace, and security perceptions index and its components are measured at the sub-regional level and are based on population groups. The methodology is based on the method that has been adopted to calculate the Global Governance Index and was applied to data from a household survey by using the governance, peace, and security module. Applying the data from the Integrated Regional Survey on Employment and the Informal Sector of the eight WAEMU member states made it possible to present perceptions of citizens, aged 18 and above, on “human rights and participation,” “rule of law,” and “peace and security.” The results indicate that individuals aged 18 and above in the WAEMU member states have good perceptions of governance, peace, and security with a perception index of 0.701. The perception of the rule of law is low (0.524), which is reflected in the low perception of the judicial system and the absence of corruption.

Generally, statistics means numerical data or quantitative information in an enquiry. In ancient times, statistics was used as ‘political arithmetic’. Some view it as branch of mathematics while others view statistics as information. Nobody is arguing on the importance of mathematics in studying statistics.

Official statistics are statistics published by the government and its agencies to make decisions about society and the economy while theoretical statistics is the application of mathematical knowledge in studying different statistical theories and methods. The importance of official statistics cannot be over-emphasized, but the graduates from many universities in developing countries, are equipped with theoretical statistics with almost no knowledge in official statistics. These graduates need to be first oriented with official statistics within National Statistics Offices (NSOs) to understand the skill, intricacies, and competencies to make sense of statistical information in areas of importance to society.

In addition, there is a need to identify gaps and various other aspects related to official statistics, which these graduates should learn, in order to be considered literate in official statistics.

This paper aims to address how to bridge the gap between official statistics and theoretical statistics to the statisticians, and hence to ensure that we leave no statistician behind because official statistics matter to all statisticians.

Data science is a concept to unify statistics, data analysis, machine learning and their related methods in order to analyze actual phenomena with data to provide better understanding. This article focused its investigation on acquisition of data science skills in building partnership for efficient school curriculum delivery in Africa, especially in the area of teaching statistics courses at the beginners’ level in tertiary institutions. Illustrations were made using Big data of selected 18 African countries sourced from United Nations Educational, Scientific and Cultural Organization (UNESCO) with special focus on some macro-economic variables that drives economic policy. Data description techniques were adopted in the analysis of the sourced open data with the aid of R analytics software for data science, as improvement on the traditional methods of data description for learning and thus open a new charter of education curriculum delivery in African schools. Though, the collaboration is not without its own challenges, its prospects in creating self-driven learning culture among students of tertiary institutions has greatly enhanced the quality of teaching, advancing students skills in machine learning, improved understanding of the role of data in global perspective and being able to critique claims based on data.

This paper aims at highlighting the lessons learned from recent initiatives between public universities of Niger and the national statistics institute.

Our investigation of the existing national statistical system revealed the need to increase the number of qualified human resources with advanced skills in open data, big data, data visualisation, machine learning, mathematical modeling and data-driven innovations.

Moreover, the existing statistical literacy and data crowdsourcing activities need to be validated and upscaled; and we have found a lack of experience in managing big data and in the development of mathematical methods and fast computational algorithms to analyze them.

Finally, the aforementioned collaboration can be improved by working closely with private sector, civil society and the data science community to generate new approaches to emerging issues including climate change and sustainable development.

Mathematics is seen by society as the foundation of scientific technological knowledge that is vital in social-economic development of a nation. In fact, studies suggest that mathematics as a subject affects all aspects of human life at different levels. This paper is a rapid systematic review of factors affecting students’ achievement in mathematics. We searched literature on student achievement in mathematics. We used ERIC database and supplemented with Google Scholar and random Google search. Twenty six articles met the final selection criteria and were reviewed. The teaching methods, teachers’ attitude, students’ attitude towards mathematics were noted as key factors in almost all articles reviewed. There seemed to be consistency too that parents can exert a positive influence on their children’s mathematical performance, classroom environment, students’ previous mathematics achievement and gender related factors. Student achievement at secondary level determines whether they will opt to or qualify to study statistics at university. From this review, it is imperative that these factors be addressed early in the students’ career so as to have more student enrollment for statistics at tertiary institutions.

The RapidSMS is an online database system which was introduced in Nigeria in 2011 as an open source software tool for monitoring birth registration process. The innovation allows real-time tracking of the local government and regional birth registration activities with the core machinery being registration at the local levels. Birth registrars are reporting aggregated numbers and registration disaggregated in four age groups < 1, 1–4, 5–9, 10–17 by sex, geographical location and by registration centre. The center-by-center data collection mechanism reflects the children’s population data indicating where birth registration coverage varies substantially between states and in some cases between local government/community setting. The dashboard is helping to identify where non-registered children likely account for some of the most excluded and vulnerable children in Nigerian communities and where rates are often lowest for such children.

These statistics are mostly found in rural areas, from poor families and with parents who have minimal or no formal education. The innovation (with its functionality improved on consistent basis) is helping to identify disparities in service delivery and facilitating prompt, evidence-based responses to areas where birth registration levels are low. It is assisting with tracking the trend of registration that will help the country reach the Sustainable Development Goals (SDGs) – birth registration-goal 16.9 by 2030. Specific focus is on how the dashboard is helping to improve data acquisition and analysis including registration coverage and not just registration events. The write up further explores how the RapidSMS is providing a platform for real-time analysis of decentralized birth registration data as an essential information for understanding efficient service delivery, improved local level registration and developing specific solutions where state level analysis and solutions are often too broad.

Studies have shown that fertility rate in Africa is still among the highest in the world. However, there are few spatial investigations into the variation of fertility rate and its determinant in Africa. This study aimed to examine the spatial distribution of fertility rate as well as highlight its significant determinants. Ordinary Least Squares (OLS) regression was carried out on dataset for 53 African countries on Total Fertility Rate (TFR) and eleven determinant factors to obtain a best model, which was then used for Geographically Weighted Regression (GWR). The study showed that TFR was significantly influenced by adolescent fertility rates, contraceptive prevalence rates and gross domestic product per capita. GWR model diagnostics of Akaike Information Criterion and adjusted R-squared showed that GWR fitted TFR in Africa better than OLS model. Also, countries around Middle to Western Africa comprising Burundi, Democratic Republic of the Congo, Central African Republic, Chad, Nigeria, Niger, Benin, Burkina Faso and Mali, were regions with high TFRs that impacted Africa’s positive TFR spatial autocorrelation. More intense works could therefore be carried out in these countries to manage the identified significant factors affecting TFR to address the negative consequences of high TFR in Africa.

Infectious diseases can inflict immense losses and suffering on the human population. As at 23 rd of June, 2020 COVID-19 pandemic has caused 20,919 cases, 25 deaths and 7,109 had recovered in Nigeria. Nigeria Centre for Disease Control (NCDC) is tracing COVID 19 carriers for designing effective control measures and to prevent the spread. Authors have modeled COVID-19 cases, but there is a dearth of information on estimating the total number of hidden COVID-19 carriers in the population. Adaptive cluster sample was used for exploring populations of hidden COVID-19 carriers. The data on daily cases of COVID-19 were extracted from NCDC website. Nigeria population was partitioned into 37 regions (states and FCT). We considered a model based approached in Bayesian framework to make inference about the number of COVID-19 carriers in Nigeria. The fitted model showed that all COVID-19 carriers will only be captured at once if contact tracing is combined with methodology designed in this work.

Businesses are getting smarter with analytics. Tax agencies across the globe are increasingly relying on digital methods to mobilize revenue. This has resulted in an unprecedented amount of citizens’ Data flowing between systems, businesses enterprises, institutions, and governments. This Data has the potential to help increase revenue collections through targeted compliance initiatives, expanding the tax base, and improving overall operational efficiency. Tax administrations, therefore have an opportunity to deliver value in this new era of digital tax by embracing enterprise initiatives and transformations that facilitate enhanced Data utilization. To enhance the use of Data analytics there is a need for a shift in mind-set around how Data is managed and analyzed. Kenya Revenue Authority implemented a transformation agenda titled ‘Towards being an insight driven Tax Authority’, aimed at drastically enhancing the Authority’s performance in a rapidly changing environment. This would see the enterprise leverage on Data warehousing, business intelligence and advanced analytical skills and tools to transform Data management and utilization. To optimize the value of analytics there has been initiatives towards integrating with big Data sources including Data sourced from third parties. This transformation can only happen if there is a deliberate initiative to build Data literacy including skills in Data mining, modelling, artificial intelligence; among others. This paper aims at exploring how a government revenue mobilization authority is transforming and is leveraging on its digital systems, big Data, and advanced analytics to enhance revenue mobilization for the government.

Agriculture is the backbone of human life, it enables for food security, health and economy. Yet, many countries in Africa suffer from poor accessibility to agriculture data which is crucial for policy makers and farmers. Half of Namibia’s population depend on agricultural activities, for as their main income source, much of which is undertaken on smallholdings. Therefore, compiling statistics around agricultural outputs is of primary concern to many national statistics agencies Unfortunately, challenges to account for agriculture crop production statistics include low frequency of data collection, lengthy data processing periods, and the lack of timely output which can be linked to policies and decision making. This paper explores the use of satellite imagery and data science techniques in a statistics agency to complement the agriculture census. The paper assessed Google Earth Engine for image processing and extracted a range of indices (NDVI, SAVI, MSAVI and GLCM and Tasseled Cap Index based) in order to identify smallholder farmers’ plots and estimate the field area in a rural village in Namibia. Although groundtruth data was not available at the time of this issue, the findings showed a promising starting point for a scaled project.

Seventeen Sustainable Development Goals (SGDs) were adopted by the World Health Organization (WHO) in 2015 for the 2030 Agenda for Sustainable Development. Sustainable Development Goal 3 (SDG3) is ‘Better health and well-being by 2030’. According to WHO, good health in the context of SDG3 is assessed with respect to the level and distribution of individuals’ and communities’ healthy life, conditions that affect health and well-being and risk factors whose presence would affect health and well-being. The overall aim is that each SDG target is achieved by 2030. In 2018 the WHO used statistical methods to assess the state of health in Africa in the context of SDG3. Their analysis revealed successes and shortfalls towards attaining SDG3. Backed by public health and other activities, statistics play an important role in improving the health and well-being of Africa. This paper explains how statistics can be used to help African countries to attain SDG3, in its role in modeling event histories, diagnosis, evidence-based medicine, determination of risk factors of exposures of morbidity and mortality, determination of risk factors of morbidity and mortality, the computation of the level and distribution of vital events, measuring disease frequency and progress, quantification of life expectancy and monitoring and evaluation.

The Convention on the Rights of the Child, Article 12, states that children have the right to be heard on matters that concern them. Animating Children’s Views (ACV) provides an innovative product for implementing Article 12 while reducing the risk that nearby adults will disagree with and punish children, a vulnerable population. We argue that national statistical offices (NSOs) should add ACV child modules to large, representative surveys, thereby becoming leaders in inclusive survey designs. This methodology uses cartoon videos with recorded voiceovers heard through headphones, followed by questions referencing the video stories (vignettes) rather than the young respondent’s own life. Proxy reporting is not used, and literacy is not presumed. Analysis of follow-up interviews and focus groups helped interpret and validate quantitative results of ACV modules piloted in Tanzania. In addition to implementing Article 12, ACV can help NSOs improve interpretation of new and existing statistical sources by including the perspectives and behavior of young people in the Global South.

In many countries, including Ethiopia, sample surveys are designed to produce estimates of variables of interest at the national and regional levels due to cost and operational considerations. For example, household food insecurity estimates are needed down at least at the zone level in Ethiopia to offer targeted solutions. However, the sample sizes of sample surveys are often not large enough to produce reliable estimates at the small area (zone) level. This paper remedies some of these shortcomings by estimating household food insecurity in each zone of Ethiopia by linking data from the 2015/16 welfare and monitoring survey and the 2007 population census using a small area estimation (SAE) approach. The results show the zonal level household food insecurity estimates generated by SAE were more efficient and precise compared to the survey-based estimates. Besides, accurate and cost-effective food insecurity statistics at the zonal level were produced without more resources through combining the available data sources. Finally, zonal level household food insecurity estimates could be the recommended tools for monitoring the progress of sustainable development goals (SDGs) in Ethiopia. Because, in the final 2030 Agenda, SDG 2 concentrates entirely on food security, recognizing much of its complex and multi-faceted nature.