Biostatistics is a field of study that pays well

Dr Daisy Salifu is a senior biostatistician and director of the biostatistics unit at the International Centre of Insect Physiology and Ecology (ICIPE) in Nairobi. PHOTO| COURTESY

What you need to know:

  • As a senior biostatistician at ICIPE, a research centre that is ever buzzing with research undertakings, Dr Salifu’s roles revolve around providing statistical support to scientists and researchers, who may include students, as they undertake their research activities in laboratories or in the field.

Dr Daisy Salifu is a senior biostatistician and director of the biostatistics unit at the International Centre of Insect Physiology and Ecology (ICIPE) in Nairobi.

Her specialisation is entomology (scientific study of insects), parasitology (scientific study of parasitic organisms) and ecology (the science of interrelationship between organisms and their environment).

Dr Salifu, a Malawian, taught applied statistics at the University of Malawi’s Bunda College before coming to Kenya in 2003. For five years, she taught statistics as a visiting lecturer at Jomo Kenyatta University of Agriculture and Technology (JKUAT), where she also earned her PhD in statistics.

In 2009, she got a job at ICIPE as a senior research assistant (biostatistician), a role she has held to date.

“Biostatistics involves the statistical processes and methods applied in the collection, analysis, and interpretation of biological data in areas such as human biology, health, and medicine. Biostatisticians derive statistical methods or models that are then used to make sensible stories out of biological or medical data,” she explains.

As a senior biostatistician at ICIPE, a research centre that is ever buzzing with research undertakings, Dr Salifu’s roles revolve around providing statistical support to scientists and researchers, who may include students, as they undertake their research activities in laboratories or in the field.

She says,

“I provide guidance to these teams at every stage of their study, from when they draft research proposals to when they execute their research projects. I also supervise the processing and analysis of the data derived from experiments. My job mainly entails ensuring that scientists stick to the research protocol.”

A research protocol, she explains, is a document that spells out the background, rationale, objectives, design, methodology, statistical considerations and organisation of a research project. Practical applications of biostatistics include medicine, food and nutrition and genetics.

“Biomedical scientists need biostatistics to test and evaluate new drugs for release. Biostatistics is applied in genetics to determine the likelihood that any given person will be affected by a hereditary disease,” she says.

“A decision on the suitability of, say, a maize variety, in certain environmental conditions is arrived at after analysing biostatistics,” she adds.

“Statistical models are used to compare prior weather conditions with current weather to predict future weather and therefore its suitability for certain food crops,” she explains.

It is also the role of biostatisticians to develop statistical methodologies to address concerns arising from medical and public health, “with the ultimate objective of improving the medical and nutritional health of the public”.

Owing to her academic background in agriculture, biological science and natural resource management, Dr Salifu finds biostatistics easier and exciting too.

“Biostatistics is the science of life. Dealing with scientists and researchers in these areas is always a thrill,” she says.

She points out that Kenya is blazing the trail in this profession in the region.

“Kenya has large pool of human resource in biostatistics compared with Malawi. Many Kenyan universities train students on statistics at both graduate and post graduate levels, leading to a large number of statisticians in the country. No Malawian universities are currently teaching statistics as an independent course,” she observes.

Training institutions have traditionally been the surest employer of biostatisticians, she explains. Lack of enough opportunities, however, has often discouraged most graduates from pursuing biostatistics fulltime.

“There are many biostatisticians running their own private consultancy companies in Kenya, which is unique. Consultancy allows more graduate biostatisticians to practice,” she says. 

After her first degree in agriculture, Dr Salifu joined the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) as a research associate in groundnut breeding. One year later, she quit to pursue a Master’s in plant breeding at the University of Malawi’s Bunda College. This would be the turning point in her career

“The university asked me to pursue statistics instead of plant breeding to tap into the then high demand in statisticians. I doubt I’d have had the opportunity to work in Kenya if I had pursued plant breeding,” she explains.

In addition to a shrunken job market, she points out, most graduate biostatisticians are unemployable, because, she argues, universities equip students with mostly theoretical knowledge without hands-on experience.

She says,

“Statistical software for data analysis are very expensive. Most of them are licensed. Smaller research institutions can’t afford them, which affects the quality of their research output. Most research institutions run on funds from donors. Donors on their part choose what research activities to fund and which ones not to.”

Implementing research recommendations is a complex process that usually takes years to effect.

Biostatistics is a well-paying job, especially for practitioners working with international research centres.

“An entry level practitioner, usually a bachelor’s degree holder, earns about Sh150, 000. A postgraduate practitioner takes home Sh200, 000 and above in basic pay. A practitioner with a PhD degree can earn between Sh300, 000 and Sh400, 000,” Dr Salifu says, adding that private data companies in the market have their own remuneration packages.

Since entering the practice more than five years ago, she has been actively involved in the technical aspect of biostatistics, contributing expertise to the profession through research activities.

“My chief career objective is to support and guide research endeavours that will help to boost food production and security to alleviate poverty in Africa. I’m also eyeing future managerial roles in the profession,” she says.

 

Who are the major employers of biostatisticians?

Locally, research institutions such as Kenya Agricultural Research Institute (KARI) and the Kenya Medical Research Institute (KEMRI) are the main employers. Internationally, there is the International Livestock Research Institute (ILRI), World Agroforestry Centre (ICRAF) and International Center for Tropical Agriculture (CIAT). Universities also hire biostatisticians as lecturers. 

 

There has been a lot of talk about big data lately. What does it entail and what are the practical applications?

This digital era has seen fast-paced evolution of data science. One such revolution is the use of ‘Big data’, which refers to large volumes of data, structured and unstructured. Unstructured data comes from information that is not organised or easily interpreted by traditional databases or data models. Examples include information contained in social media posts and data streamed from sensors. Structured data is information from open sources such as data from Demographic Household Surveys (DHS), business sales records and results from scientific experiments. Big data is timely, vast and cost effective, which helps to produce quality analytics that provide useful insights.

Big data helps to mitigate risks and, therefore, make smart business decisions through proper risk analysis. It has been explored to monitor Sustainable Development Goals (SDGs) in the search for better results. 

 

How does one flourish in biostatistics?

First, you must be a team player because scientists work in teams. You must also be a good communicator who can articulate statistical concepts in terms that can be understood by even non-statisticians. Research should be fool proof, you can’t gloss over phenomena, so attention to detail at every stage of the study is important.