Main Article Content



The annual mortality rate (per 1,000 live births) from 1960 to 2017 of Pakistan is the subject of this paper. As a reason, in South Asia, Pakistan contributed the most to childhood mortality, including infant mortality. Despite progress, child mortality has declined globally, but Pakistan is still struggling and far behind the targets of the Sustainable Development Goals. There are several reasons for high childhood mortality, including socioeconomic determinants and lack of effective implementation of health-related policies, particularly in primary health care settings. In the present study, we use stochastic univariate models to uncover the trend of infant mortality by using more than half a century of data from 1960–2017. The secondary data related to the mortality rate (per 1,000 live births) from 1960 to 2017 was extracted from the World Bank Dataset. Descriptive and time series analysis (Box-Jenkins) are applied. The analysis is carried out using the R programming language.

Forecast, infant mortality rate in Pakistan, time series model

Article Details

How to Cite
NASIR, J. A., CHESNEAU, C., IMRAN, M., & JAMAL, F. (2021). A STUDY ON MORTALITY RATE FOR INFANT IN PAKISTAN: AN APPLICATION OF BIOSTATISTICS. Asian Journal of Advances in Research, 11(3), 38-47. Retrieved from http://mbimph.com/index.php/AJOAIR/article/view/2533
Original Research Article


WHO: World Health Organization, Infant mortality situation and trends; 2017. Available:https://www.who.int/gho/child_health/mortality/neonatal_infant_text/en/

UNIGME: ‘Levels & Trends in Child Mortality: Report 2018, Estimates developed by the United Nations Inter-agency Group for Child Mortality Estimation’, United Nations Children’s Fund, New York; 2018.

UNIGME: Levels & Trends in Child Mortality: Report 2017: Estimates Developed by the UN Inter-Agency Group for Child Mortality Estimation: United Nations Children's Fund, 2017.

Gallup: Gallup report of infant mortality 1980-2018, Pakistan; 2018. Available:http://gallup.com.pk/wp-content/uploads/2018/04/Infant-mortality-PR-1.pdf

Khadka KB, Lieberman LS, Giedraitis V, Bhatta L, Pandey G. The socio-economic determinants of infant mortality in Nepal: analysis of Nepal Demographic Health Survey, 2011. BMC Pediatrics. 2015;15:152.

Liu Y, Chen Y, Wang D: Economic and socioeconomic determinants of infant mortality: A cross-country investigation; 2015.

Lamichhane R, Zhao Y, Paudel S, Adewuyi EO: Factors associated with infant mortality in Nepal: a comparative analysis of Nepal demographic and health surveys (NDHS) 2006 and 2011. BMC Public Health. 2017;17:53.

Zahid GM. Mother's health-seeking behaviour and childhood mortality in Pakistan. The Pakistan Development Review. 1996;719-31.

Iram U, Butt MS: Socioeconomic determinants of child mortality in Pakistan: Evidence from sequential probit model. International Journal of Social Economics. 2008;35:63-76.

NIPS: National Institute of Population Studies (NIPS) [Pakistan] and ICF. 2019. Pakistan Demographic and Health Survey 2017-18. Islamabad, Pakistan, and Rockville, Maryland, USA: NIPS and ICF; 2017-18.

Helova A, Hearld KR, Budhwani H: Associates of neonatal, infant and child mortality in the Islamic Republic of Pakistan: a multilevel analysis using the 2012–2013 demographic and health surveys. Maternal and Child Health Journal. 2017;21:367-75.

Shumway RH, Stoffer DS. Time series analysis and its applications: with R examples: Springer; 2017.

Carnes BA, Olshansky SJ, Grahn D: Continuing the search for a law of mortality. Population and Development Review 1996:231-64.

Willemse W, Koppelaar H. Knowledge elicitation of Gompertz'law of mortality. Scandinavian Actuarial Journal. 2000, 2000:168-79.

Keyfitz N. Choice of function for mortality analysis: Effective forecasting depends on a minimum parameter representation. Theoretical Population Biology. 1982;21:329-52.

Carroll GR. A stochastic model of organizational mortality: Review and reanalysis. Social Science Research. 1983; 12:303-29.

Lin XS, Liu X. Markov aging process and phase-type law of mortality. North American Actuarial Journal. 2007;11:92-109.

Brockwell PJ, Davis RA, Calder MV: Introduction to time series and forecasting: Springer; 2002.

Van Weel C, Kassai R, Qidwai W, Kumar R, Bala K, Gupta PP, Haniffa R, Hewageegana NR, Ranasinghe T, Kidd M: Primary healthcare policy implementation in South Asia. BMJ Global Health. 2016;1:e000057.

Aziz SZ, Hanif I: Primary care and health system performance in Pakistan: A study of basic health units of South Punjab. J Pak Med Assoc. 2016;66:1632-6.

McAllister DA, Liu L, Shi T, Chu Y, Reed C, Burrows J, Adeloye D, Rudan I, Black RE, Campbell H. Global, regional, and national estimates of pneumonia morbidity and mortality in children younger than 5 years between 2000 and 2015: a systematic analysis. The Lancet Global Health. 2019;7:e47-e57.

Naghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, Aboyans V, Adetokunboh O, Afshin A, Agrawal A: Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 2017; 390:1151-210.

UNICEF: United Nations Children’s Fund (UNICEF), World Health Organization, International Bank for Reconstruction and Development/The World Bank. Levels and trends in child malnutrition: key findings of the 2019 Edition of the Joint Child Malnutrition Estimates. Geneva: World Health Organization; 2019.

Huffman SL, Zehner ER, Victora C: Can improvements in breast-feeding practices reduce neonatal mortality in developing countries? Midwifery. 2001;17:80-92.

Victora CG, Smith PG, Vaughan JP, Nobre LC, Lombardi C, Teixeira AMB, Fuchs SC, Moreira LB, Gigante LP, Barros FC: Infant feeding and deaths due to diarrhea: a case-control study. American Journal of Epidemiology. 1989;129:1032-41.

Katz J, Lee AC, Kozuki N, Lawn JE, Cousens S, Blencowe H, Ezzati M, Bhutta ZA, Marchant T, Willey BA: Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: a pooled country analysis. The Lancet. 2013; 382:417-25.

Organization WH: Survive and thrive: transforming care for every small and sick newborn: key findings. Survive and thrive: transforming care for every small and sick newborn: key findings; 2018.

Jamal F, Chesneau C, Aidi K, Ali A. Theory and application of the power ailamujia distribution. Journal of Mathematical Modeling. 2021;9(3):391-413.

Afify AZ, Cordeiro GM, Ibrahim NA, Jamal F, Elgarhy M, Nasir MA. The marshall-olkin odd burr III-G family: Theory, estimation, and engineering applications. IEEE Access. 2021;9:4376-4387.

Abdulhakim A. Al-Babtain, Rehan AK Sherwani, Ahmed Z. Afify, Khaoula Aidi, M. Arslan Nasir, Farrukh Jamal, Abdus Saboor. The extended Burr-R class: Properties, applications and modified test for censored data. 2021;6(3):2912-2931.

Ramadan A ZeinEldin, Christophe Chesneau, Farrukh Jamal, Mohammed Elgarhy , Abdullah M. Almarashi, Sanaa Al-Marzouki. Generalized truncated frechet generated family distributions and their applications. 2021;126(2):791-819.

Naeem S, Ali A, Chesneau C, Tahir MH, Jamal F, Sherwani RAK, Ul Hassan M. The classification of medicinal plant leaves based on multispectral and texture feature using machine learning approach. Agronomy. 2021;11:263.

Al-Marzouki S, Jamal F, Chesneau C, Elgarhy M. Half logistic inverse lomax distribution with applications. Symmetry. 2021;13(2):309. Available:https://doi.org/10.3390/sym13020309

Al-Marzouki, Sanaa, Christophe Chesneau, Sohail Akhtar, Jamal Abdul Nasir, Sohaib Ahmad, Sardar Hussain, Farrukh Jamal, Mohammed Elgarhy, El-Morshedy M. Estimation of finite population mean under PPS in presence of maximum and minimum values. AIMS Mathematics. 2021;6(5):5397-5409.

Bantan Rashad, Amal S Hassan, Ehab Almetwally, Elgarhy M, Farrukh Jamal, Christophe Chesneau, Mahmoud Elsehetry. Bayesian analysis in partially accelerated life tests for weighted lomax distribution. CMC-Computers Materials & Continua. 2021; 68(3):2859-2875.

Khan Sherwani, Muhammad Waqas, Nadia Saeed, Muhammad Farooq, Muhammad Ali Raza, Farrukh. Transmuted inverted kumaraswamy distribution: Theory and applications Rehan Ahmad. Jamal Punjab University Journal of Mathematics. 2021;53(3):29-45.

Aqib Ali, Wali Khan, Naeem Mashwani, Uddin Samreen, Muhammad Irfan, Wiyada Kumam, Poom Kumam, Hussam Alrabaiah, Farrukh Jamal, Christophe Chesneau. COVID-19 infected lung computed tomography segmentation and supervised classification approach. Computers, Materials, & Continua. 2021;391-407.

Farooq M, Sarfraz S, Chesneau C, Ul Hassan M, Raza MA, Sherwani RAK, Jamal F. Computing expectiles using k-nearest neighbours approach. Symmetry. 2021;13:645. Available:https://doi.org/10.3390/sym13040645

Abdullah Ali H. Ahmadini, Wali Khan Mashwani, Rehman Ahmad Khan Sherwani, Shokrya S. Alshqaq, Farrukh Jamal, Miftahuddin Miftahuddin, Kamran Abbas, Faiza Razaq, Mohammed Elgarhy, Sanaa Al-Marzouki. Estimation of constant stress partially accelerated life test for fréchet distribution with type-I censoring. Mathematical Problems in Engineering. 2021;Article ID 9957944:8.

Jamal F, Chesneau C, Bouali DL, Ul Hassan M. Beyond the Sin-G family: The transformed Sin-G family. PLoS ONE. 2021;16(5):e0250790. Available:https://doi.org/10.1371/journal.pone.0250790

Bantan R, Elsehetry M, Hassan AS, Elgarhy M, Sharma, D, Chesneau C, Jamal F. A two-parameter model: Properties and estimation under ranked sampling. Mathematics. 2021; 9:1214. Available:https://doi.org/10.3390/math9111214

Almarashi AM, Khan K, Chesneau C, Jamal F. Group acceptance sampling plan using marshall–olkin kumaraswamy exponential (MOKw‐E) distribution. Processes. 2021; 9:1066. Available:https:// doi.org/10.3390/pr9061066

Muhammad Mohsin, Shafaqat Mehmood, Farrukh Jamal, Muhammad Mushahid Anwer. Modeling and forecasting of declining area and production of mango orchards in district Bahawalpur, Pakistan: A case of tehsil ahmedpur east. J Agric. Res. 2021;59(2):197-212.

Muhammad Rasheed, Khadija Noreen, Rashid Ahmed MH Tahir, Farrukh Jamal. Some useful classes of minimal weakly balanced neighbor designs in circular blocks of two different sizes, Communications in Statistics - Theory and Methods; 2021. DOI: 10.1080/03610926.2021.1975135

Bantan, Rashad AR, Christophe Chesneau, Farrukh Jamal, Ibrahim Elbatal, Mohammed Elgarhy. The truncated burr XG family of distributions: Properties and applications to actuarial and financial data. Entropy. 2021;23(8):1088.

Algarni Ali, Abdullah M Almarashi, Farrukh Jamal, Christophe Chesneau, aMohammed Elgarhy. Truncated inverse lomax generated family of distributions with applications to biomedical data. Journal of Medical Imaging and Health Informatics. 2021;11(9):2425-2439.

Bantan, Rashad AR, Farrukh Jamal, Christophe Chesneau, Mohammed Elgarhy. Theory and applications of the unit gamma/gompertz distribution. Mathematics. 2021;9(16):1850.

Bantan RA, Jamal F, Chesneau C, Elgarhy M. Type II Power Topp-Leone Generated Family of Distributions with Statistical Inference and Applications. Symmetry. 2020;12(1):75.

Al-Marzouki S, Jamal F, Chesneau C, Elgarhy M. Type II topp leone power lomax distribution with applications. Mathematics. 2020;8(1):4.

Jamal F, Chesneau C, Elgarhy M. Type II general inverse exponential family of distributions. Journal of Statistics and Management Systems. 2020;23(3):617-641.

Chesneau C, Jamal F. On a new special member of the Weibull-X family of distributions. Eurasian Bulletin of Mathematics (ISSN: 2687-5632). 2020;3(2):56-72.

Shah MAA, Mashwani WK, Kumam W, Kumam P, Chesneau C, Jamal F, Khan HU. Application of mixed sampling to real life data: A case study on socio-economic determinants by using SEM and CFA Techniques. Mathematics. 2020;8(3):337.

Bantan RA, Zeineldin RA, Jamal F, Chesneau C. Determination of the factors affecting king Abdul Aziz University Published Articles in ISI by Multilayer Perceptron Artificial Neural Network. Mathematics. 2020;8(5):766.

Al-Marzouki S, Jamal F, Chesneau C, Elgarhy M. Erratum: Al-Marzouki, S., et al. Type II Topp Leone Power Lomax Distribution with Applications. Mathematics 2020, 8, 4. Mathematics. 2020;8(6):871.

Bantan RA, Elgarhy M, Chesneau C, Jamal F. Estimation of entropy for inverse lomax distribution under multiple censored data. Entropy. 2020;22(6):601.

Ali A, Qadri S, Mashwani WK, Brahim Belhaouari S, Naeem S, Rafique S, Anam S. Machine learning approach for the classification of corn seed using hybrid features. International Journal of Food Properties. 2020;23(1):1110-1124.

Ali A, Qadri S, Khan Mashwani W, Kumam W, Kumam P, Naeem S, Sulaiman M. Machine learning based automated segmentation and hybrid feature analysis for diabetic retinopathy classification using fundus image. Entropy. 2020;22(5):567.

Naeem S, Ali A, Qadri S, Mashwani WK, Tairan N, Shah H, Anam S. Machine-learning based hybrid-feature analysis for liver cancer classification using fused (MR and CT) images. Applied Sciences. 2020;10(9):3134.

Jamal F, Reyad HM, Ahmed SO, Ali Shah SMA. Mathematical properties and applications of minimum gumbel burr distribution. NED University Journal of Research. 2020;17(2):1-14.

Jamal F, Bakouch HS, Nasir MA. Odd burr III G-Negative binomial family with application. Journal of Testing and Evaluation. 2020;49(5):1-21.

Handique L, Jamal F, Chakraborty S. On a family that unifies Generalized Marshall-Olkin and Poisson-G family of distribution. Accepted Manuscript, arXiv preprint arXiv:2006.05816; 2020.

Bantan RA, Jamal F, Chesneau C, Elgarhy M. On a new result on the ratio exponentiated general family of distributions with applications. Mathematics. 2020;8(4):598.

Bantan RA, Chesneau C, Jamal F, Elgarhy M. On the Analysis of New COVID-19 cases in pakistan using an exponentiated version of the M family of distributions. Mathematics. 2020;8(6):953.

Almarashi AM, Badr MM, Elgarhy M, Jamal F, Chesneau C. Statistical inference of the half-logistic inverse rayleigh distribution. Entropy. 2020;22(4):449.

Almarashi AM, Elgarhy M, Jamal F, Chesneau C. The exponentiated truncated inverse weibull-generated family of distributions with applications. Symmetry. 2020;12(4):650.

Chesneau, C, Tomy L, Gillariose J, Jamal F. The inverted modified Lindley distribution. Journal of Statistical Theory and Practice. 2020;14(3):1-17.

Chakraborty S, Handique L, Jamal F. The Kumaraswamy Poisson-G family of distribution: its properties and applications. Annals of Data Science. 2020;7(4):1-19.

Nasir MA, Tahir MH, Chesneau C, Jamal F, Shah MAA. The odds generalized gamma-G family of distributions: Properties, regressions and applications. Statistica. 2020;80(1):3-38.

Reyad H, Jamal F, Özel G, Othman S. The Poisson exponential-G family of distributions with properties and applications. Journal of Statistics and Management Systems. 2020;23(7):1-24.

Badr MM, Elbatal I, Jamal F, Chesneau C, Elgarhy M. The transmuted odd fréchet-G family of distributions: Theory and applications. Mathematics. 2020;8(6):958.

Aldahlan MA, Jamal F, Chesneau C, Elgarhy M, Elbatal I. The truncated Cauchy power family of distributions with inference and applications. Entropy. 2020;22(3):346.

Al-Marzouki S, Jamal F, Chesneau C, Elgarhy M. Topp-leone odd fréchet generated family of distributions with applications to COVID-19 data sets. Computer Modeling in Engineering & Sciences. 2020;125(1):437-458.

Bantan RA, Jamal F, Chesneau C, Elgarhy M. Type II power topp-leone generated family of distributions with statistical inference and applications. Symmetry. 2020;12(1):75.

Jamal F, Chesneau C, Elgarhy M. Type II general inverse exponential family of distributions. Journal of Statistics and Management Systems. 2020;23(3):617-641.

Al-Babtain AA, Elbatal I, Chesneau C, Jamal F. Box-Cox gamma-G family of distributions: Theory and applications. Mathematics. 2020; 8(10):1801.

Bantan RA, Chesneau C, Jamal F, Elgarhy M, Tahir MH, Ali A, Anam S. Some new facts about the unit-rayleigh distribution with applications. Mathematics. 2020;8(11):1954.

Gillariose J, Tomy L, Jamal F, Chesneau C. The Marshall-olkin modified lindley distribution: Properties and applications. Journal of Reliability and Statistical Studies. 2020;13(1):177-198.