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Dog-related practices among rural communities in the Kilosa District, Tanzania: implications for rabies prevention interventions
Get PDFA Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of
Master of Science in Public Health Research at the Nelson Mandela African Institution
of Science and TechnologyRabies is a disease which is most transmitted to humans through infected domestic dog bites.
The disease is preventable through mass dog vaccination (MDV) or timely access to Postexposure
Prophylaxis
(PEP)
injections
for
humans.
Accessing
a
full
course
of
PEP,
however,
is
a
challenge,
due
to
high
costs
and
lack
of
availability.
In
Africa,
rural
populations
are
most
affected
by rabies; this is also the case in Tanzania. Since the group who is most at risk of
exposure are children, emphasizing correct dog handling practices, for example, can
minimize dog bites and hence prevent disease incidences. MDV of the susceptible canine
population is the best way of breaking the disease transmission cycle, but achieving the
recommended coverage of 70% is still a challenge. To rectify this, it is important to
understand dog ownership systems, management and handling practices and the decisionmaking
process within households. The current study identified these to help addressing
constraints related to rabies prevention and control in the community. The study focused on
characteristics of dog ownership in the household (HH), decision-making process regarding
dog ownership, dog vaccination and access to PEP for a child once exposed. A crosssectional
study conducted in Kilosa district between May 2016 and March 2017, looked at
1216 households in rural communities in Tanzania. The findings elucidated significant
factors affecting dog ownership and the number of dogs kept per household. Larger
households are more likely to own dogs <0.001. While a child is likely to take the dog for
vaccination, the decision to vaccinate the dog is usually made by the father. The findings also
showed that mothers are responsible for the child's health once exposed and take the child to
access PEP. The research findings will help to understand HH decision making with regards
to dog ownership and responsibility for child health. These results are relevant for the design
and implementation of rabies interventions and other zoonoses
Iodine status and dietary habits among Primary School children in Kinondoni, Tanzania
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of
Master’s in Life Sciences of the Nelson Mandela African Institution Sciences and
TechnologyTanzania is one of the countries where excessive iodine intake has been reported; hence
intervention and identification of possible causes is required. The present study assessed iodine
status and determined the critical contributors to excessive iodine intake in school children
from Kinondoni, Tanzania. A total of 322 pupils and 30 food vendors provided salt samples
for iodine analysis. Urinary iodine concentration (UIC) was spectrophotometrically determined
in 266 sub-sampled children using the ammonium-persulfate digestion method. Information on
dietary habits was collected using the Food Frequency Questionnaire and 24 hours dietary
recall. Anthropometric values were determined by measuring children’s height and weight.
Moreover, Knowledge, Attitude, and Practices study was done using a modified specific iodine
deficiency-related questionnaire. Of the salt samples, 87% were adequately iodized with mean
53.94 ± 13.02, indicating over iodization. The median UIC was 401 µg/L, signifying excessive
iodine intake. Twelve percent were overweight or obese and only 46.6% of pupils and 53.3%
of food vendors had good knowledge of iodized salt utilization. Discretionary salt use (67.3%),
higher consumption of potato chips (53.5%) and fried cassava (59.0%) were associated with a
higher risk of excessive iodine intake. Potato chips (Adjusted Odds Ratio [AOR] =9.04, 95%
CI: 3.61-22.63) and fried cassava consumption for 4-7 days/week (AOR=11.08, 95% CI: 3.45-
35.54) were significantly associated with excessive iodine intake. Discretionary salt intake
significantly contributes to the high iodine status of schoolchildren in the study area. This effect
can be reduced by public health campaigns to decrease salt consumption and improve salt
iodation practices
Development of an intelligent tracking system for monitoring rhinos and elephants: A case study of Ngorongoro conservation area
Get PDFA Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of
Doctor of Philosophy in Information and Communication Science and Engineering of the
Nelson Mandela African Institution of Science and TechnologyEvents such as poaching, accidents, unexpected adverse health events (e.g., heart problems,
seizures, heart stroke, dizziness, breathing problems, bleeding and broken bones) have adverse
impact on animals’ health. Many of such events, if known to someone in a position to assist the
animal, can be avoided, minimized or ameliorated. Unfortunately, many events occur in a
manner in which assistance is unavailable or provided too late. In regard to this, measures
needed include improving systems and methods for avoiding or reducing the impact of such
adverse events.
The study developed an intelligent real-time tracking system for monitoring rhinos and
elephant. It was guided by four specific objectives: reviewing and analyzing the existing
systems for tracking animals and proposing new more intelligent systems, designing of smart
sensing system for animal emotions recognition, developing computational models’ analysis
of wildlife tracking system for optimality, and developing an intelligent wildlife collar
information management system using mobile application. The first objective was
accomplished by conducting a cross-sectional study, and one-time data collection at
Ngorongoro Conservation Area, Tanzania. The second objective was completed by designing a
modern smart sensing animal collar belt that can recognize animal emotions. The third objective
was performed by attenuation models-based analysis of wildlife tracking system for optimality.
And the fourth objective was accomplished by developing a mobile application that collects
periodical sensor output responses from tracked elephant/rhino with their GPS locations.
All developed solutions were promising and can be utilized on improvement of the current
existing ant-poaching system. The solutions can be considered as a proof of concept, which needs
to be developed further for use in final product
Performance optimization of unplanned water distribution networks in fast growing towns: a case study of Mwanza city, Tanzania
Get PDFA Dissertation Submitted in Partial Fulfilment of the Requirements for the Masters
Degree in Hydrology and Water Resources Engineering of the Nelson Mandela African
Institution of Science and TechnologyHigh Non-Revenue Water (NRW) and unreliable water supply services are major challenges in
operations of the water networks in most of the fast-growing cities in developing countries. The
present study aims at investigating the extent that the existing distribution network contributes
to the prevailing high percentage of the NRW; and explore optimization scenarios focusing on
water loss reduction and system improvement in the unplanned network. The measured system
flow and pressure were used for water balance assessment, calibration and modelling to
simulate different scenarios in order to improve system performance. The results showed 52%
of the junctions in the system had high pressure above recommended which contributed to 87%
of real loss and 83% of pipes had low velocities below the set thresholds. These indicate that
uneven distribution of pressures and velocities are driven by improper topology of both pipe
sizing and supply directions in the unplanned network. About 50% of NRW was detected in
the study area while the entire network had 37%, thus small areas assessment and pressure
management are required. The pressure reduction by optimizing installation of pressure
reducing valves and change network topology reduced NRW by 46%. In addition, regular nodal
hydraulic analysis and flow modifications performed well when integrated with stochastic town
growth for system capacity torelance. The study provides ways for sustainably improving the
poorly performing water networks in fast-growing towns. It also recommends methods of
integrating pressure management, network topology change and resilient to future demand for
attaining a better system performance
A Review on Papaya Mealybug Identification and Management Through Plant Essential Oils
Get PDFThis research published by Oxford University Press, 2021Papaya (Carica papaya L.) production suffers from a multitude of abiotic and biotic constraints, among those are
insect pests, diseases, and environmental conditions. One of the seriously damaging pests of papaya is invasive
papaya mealybug, Paracoccus marginatus, which can inflict heavy yield loss if not contained. Little information
on papaya mealybug species has been documented due to challenges in identification approaches to species
level. The current approach is based on the morphological features which are restricted to the mealybug life cycle
leading to unclear identification. In Sub-Saharan Africa, where a wide diversity of mealybug species exists, it is
essential to have a correct identification of these insect species due to the specificity of control measures. Molecular
identification could be the best way to identify the mealybug at the species level. Presently, farmers rely heavily
on chemical pesticides as their only available option for papaya mealybug control. The overuse of pesticides due
to insect waxy covering has led to the development of pesticide resistance and the negative impact on the local
ecosystem. Alternatively, the use of plant essential oils (EOs) with adjuvant is suggested as the safe solution to
papaya mealybug control as they contain a rich source of natural chemicals that dissolve the insect wax layer,
causing the cell membrane to rupture eventually leading to death. This review provides current research knowledge
about the papaya mealybug identification approaches and plant EOs from Sweet orange, garlic, castor, and adjuvant
(isopropyl alcohol, and paraffin) as sustainable papaya mealybug management
Internet of things based system for environmental conditions monitoring in poultry house: A case of Tanzania
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of
Master’s In Information and Communication Science and Engineering of the Nelson
Mandela African Institution of Science and TechnologyPoultry health is imperative for the continued growth of poultry and increased production.
Environmental conditions such as temperature, humidity, and Ammonia gas impact the health
of the poultry; whereby, they can affect the respiratory system and eventually cause death. In
Tanzania, most farmers use charcoal and kerosene stoves to control these parameters as they
have limited access to economical, secure, and user-friendly poultry house monitoring
systems. However, such traditional methods are not environmentally friendly, unreliable,
difficult to manage, and inaccurate. In addition to that, many smart poultry monitoring
platforms proposed by previous studies are not centralized, thus making the system being not
scalable and costly. For example a farmer with three distributed coops needs three monitoring
platforms to monitor the coops while only single platform could suffice. Therefore, this study
proposes an Internet of Things (IoT) based system for environmental conditions monitoring
in the poultry house to address the aforementioned challenges. The survey was conducted in
Arusha and Kilimanjaro regions respectively to determine the strength and weakness of the
traditional methods used by poultry farmers, perception towards the proposed system and
identify the requirements needed to develop the proposed an IoT based system. The study
used Jupyter Notebook powered by Anaconda package manager and the Python language for
data analysis. Based on the requirements gathered from the survey, the prototype that is
divided into two four parts; sensing, aggregation, transmission and monitoring part was
developed, where the hardware components were selected based on the cost, open source,
availability in local market, Quality of Service (QoS), throughput and latency criteria. The
developed prototype was deployed in the field to verify and validate its performance. This
activity was done in seven days consecutively and the results indicated that the system would
save both small scale and large scale farmers in terms of time and labor costs as Farmer can
monitor and control the poultry house conditions securely, reliably, and remotely. The study
also proposes an algorithm to allow the system to work online, and offline (i.e., synchronizing
with the cloud server when the Internet access is available)
A predictive model for early detection of diabetes mellitus using machine learning
Get PDFA Project Report Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyDiabetes is a chronic, metabolic disease characterized by elevated levels of blood glucose or
blood sugar that over time can bring severe damage to vital organs including the heart, blood
vessels, eyes, kidneys and nerves. Diabetes is therefore one of the major priorities in medical
science research. Type 2 diabetes is common in adults, either because of inadequate insulin
production, or when the body’s cells fail to respond properly to the produced insulin. For all the
diabetes cases, it’s found out that 90% are Type 2 diabetes. Of the 422 million people with
diabetes worldwide, 336 million people are found in developing countries, and 1.6 million
people die of diabetes each year according to statistics by the World Health Organization.
Around 19.8 million adults in Africa have Type 2 diabetes but approximately 75% are unaware
of their condition (undiagnosed). Most people are undiagnosed because many people lack
knowledge of symptoms for diabetes, and others are not diagnosed due to lack of testing kits
more especially in rural areas. African governments have scaled up purchasing and distribution
of diagnostic kits but the majority of the population has not been reached. Researchers have
been developing predictive models for Type 2 diabetes, but African populations are not widely
included in their datasets. The developed models may therefore not accurately identify at-risk
populations in the African context. The main emphasis of this research was to come up with a
machine learning prediction model to find out Ugandans likely to be suffering from Type 2
diabetes (output classes: high risk or low risk), based on input symptoms.
Random Forest, Support Vector Machine, Naïve Bayes, and AdaBoost classifiers were trained
on anonymised, real patient data with twelve features including age, gender (male or female),
systolic blood pressure, residence (town or village), diastolic blood pressure, family Member
with diabetes, alcohol intake, smoker, hypertensive, obesity, physically inactive and body mass
index. This research’s experimental results after the comparison of the Accuracy Score and
Confusion Matrix for all the above algorithms, the Random Forest classifier emerged the
premier with the accuracy score of 85.4%, thus the experimental results shown that
performance of Random Forest classifier as being significant superior compared to all other the
machine learning algorithms
Maternal knowledge-seeking behavior among pregnant women in Tanzania
Get PDFThis research article was published by SAGE Publications Ltd, 2021Background:
Maternal mortality continues to be a global challenge with about 830 women dying of childbirth and pregnancy complications every day. Tanzania has a maternal mortality rate of 524 deaths per 100,000 live births.
Objective:
Knowing symptoms associated with antenatal risks among pregnant women may result in seeking care earlier or self-advocating for more immediate treatment in health facilities. This article sought to identify knowledge-seeking behaviors of pregnant women in Northern Tanzania, to determine the challenges met and how these should be addressed to enhance knowledge on pregnancy risks and when to seek care.
Methods:
Interview questions and questionnaires were the main data collection tools. Six gynecologists and four midwives were interviewed, while 168 pregnant women and 14 recent mothers participated in the questionnaires.
Results:
With the rise in mobile technology and Internet penetration in Tanzania, more women are seeking information through online sources. However, for women to trust these sources, medical experts have to be involved in developing the systems.
Conclusion:
Through expert systems diagnosis of pregnancy complications and recommendations from experts can be made available to pregnant women in Tanzania. In addition, self-care education during pregnancy will save women money and reduce hospital loads in Tanzania
Diversity and quantity of macro-and microplastics in irrigation farms sourcing water from an urban river: a case of Arusha Tanzania
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master’s in Hydrology and Water Resources Engineering of the Nelson Mandela African Institution of Science and TechnologyIncreased concentration of plastics in urban rivers and agricultural farms causes degradation
of river system functionality and reduces the productivity of agricultural soils, respectively.
This study assessed the quantity and types of macro-and microplastics found in dependent
smallholder irrigation farms downstream of Arusha city in Tanzania. The microplastics'
concentration from the sites was visualized using dissecting microscope 40X, enumerated and
categorized based on the shape, color, and sizes for soil samples. Then the suspected materials’
spectral were determined using the Attenuated Total Reflectance- Fourier Transform Infrared
(ATR-FTIR). Afterwards, the confirmations and identifications of the polymers' types from
spectral were confirmed using SiMPle Software. The average microplastic from the water
column was 0.57 ± 0.27 items L-1
, sediment 0.17± 0.07 items g-1, while in the irrigation farms
ranged from 102 to 728 items with a mean of 0.69 ± 0.35 items g-1
. However, no international
standards have been developed to ascertain the pollution level, but the reported values are
unsafe to the environment. Other studies conducted in similar conditions reported mean values
within the range of values found in this study and more. Polyethylene was the dominating type
of macroplastics evaluated from riverbanks and irrigation farms with a frequency of occurrence
100 %, while polystyrene was abundant in all microplastics samples. Farms adjacent to the
irrigation canal had a greater number of microplastics and macroplastics. Thus this study
reveals urban rivers as the primary sources of plastics pollution in the irrigation farms situated
in flood-prone zones
Momputational analysis of MHD blood flow through a stenosed artery in the presence of body acceleration and chemical reaction
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mathematical and Computer Sciences and Engineering of the Nelson Mandela African Institution of Science and TechnologyThe unsteady, laminar and two-dimensional pulsatile flow of both, Newtonian and non Newtonian chemically reacting blood in an axisymmetric stenosed artery subject to body ac celeration and magnetic fields were studied. In the case of non-Newtonian blood, heat transfer
was taken into consideration. The combined effects of body acceleration, magnetic fields and
chemical reaction on blood flow were considered. The non-Newtonian model was chosen to
suit the Herschel-Bulkley fluid characteristics.
The non-dimensional governing equations were solved using the explicit finite difference
method and executed using MATLAB package. The solutions showing the velocity, temper ature and concentration profiles were illustrated. The effects of Reynolds number, Hartman
number, Schmidt number, Eckert number and Peclet number were examined. Additionally, the
effects of stenosis and body acceleration on blood flow were explored.
The study found that, body acceleration, magnetic fields and stenosis affect the normal flow
of blood. Body acceleration was observed to have more effect on blood flow than the mag netic fields and stenosis. Furthermore, as the key findings of the study, it was noticed that the
combined effect of stenosis, body acceleration, magnetic field and chemical reaction, reduce
the concentration profile of the blood flow and the blood flow velocity. It was also observed
that, the axial velocity, concentration and skin friction, decrease with increasing stenotic height.
The velocity on the other hand increased as the body acceleration increased. Furthermore, as
the Hartman number increased, both the radial and axial velocities diminished. The higher the
chemical reaction parameter was, the lower were the concentration profiles.
For the non-Newtonian blood, the velocity profile diminished with increase in the Hartman
number and increased with the body acceleration. The temperature profile was observed to
rise by the increase of body acceleration and the Eckert number, while it diminished with the
increase of the Peclet number. It was also found that, the concentration profile increased with
the increase of the Soret number and decreased with the increase of the chemical reaction. It
was further observed that the shear stress deviated more when the power law index, n > 1 than
when n < 1