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Perception and Risk Factors Associated with Tuberculosis in the Manyara Region, Tanzania2
Get PDFA research article is submitted to Zoonotic Disease 2023, volume 3Tuberculosis (TB) results from infection with members of the Mycobacterium tuberculosis complex (MTBC) and represents a major global public health concern. We here sought to assess the perceptions of human and animal TB and the prevalence of circulating MTBCs lineages and associated risk factors through a cross-sectional survey of 335 individuals presenting with symptoms of pulmonary or extrapulmonary TB in the Manyara region of Tanzania. After the enrollment of participants, a questionnaire survey was conducted, samples were collected for bacterial culture, and real-time multiplex PCR was performed to differentiate amongst primary animal and human MTBC lineages. The results show poor TB awareness: 31.6% of the participants were not aware of human TB; 82.4% were unaware of animal TB and 95.2% lacked awareness of zoonotic TB (zTB) transmission. A total of 18 recovered specimens (5%; 95% CI: 3–8%) were positive by culture, all of which were typed as M. tuberculosis sensu stricto using a lineage-specific PCR assay. While no single risk factor was significantly associated with MTBC culture positivity, the survey revealed considerable self-reported high-risk practices for contracting zTB. Together, the results show that Manyara residents have poor knowledge of diseases caused by MTBCs and high evidence of risky practices for contracting zT
Remediation of soils contaminated with fluoride using seaweed-derived materials: case of slopes of mount Meru
Get PDFA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Materials Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyWhile exposure to low fluoride is essential for stronger bones and teeth, exposure to high
concentration (> 3 mg/L/day) leads to hyperostosis and osteoporosis. This research evaluated
the role of fertilizer application on soil’s fluoride release, and assess the effectiveness of using
seaweed (Eucheuma cottonnii) derived materials for remedial purposes. The soil
characterization results in the study area, indicated the availability of diverse fluoride fractions
and in different quantities in the soil such that; water-soluble (Ws-F) (39.5 ± 0.5 mg/kg),
Exchangeable (Ex-F) (3.5 ± 0.5 mg/kg), bound to iron/manganese (Fe/Mn-F) (3.1 ± 1.0 mg/kg),
and organic matter bound (Or-F) (9.1 ± 2.1 mg/kg) fluoride whereas the total fluoride (Tot-F)
was 422 ± 52.9 mg/kg. The study further reports that the use of three studied fertilizers
(diammonium phosphate (DAP), Urea, and farmyard manure) accelerates the bioavailability of
fluoride in the soil by increasing Ws-F. These results deliver alerts to the plant health regulators
suggesting proper management of the quality of fertilizers used for the enhancement of crop
quality particularly those used in fluoride-contaminated agricultural soils. While fertilizer
application accelerated the bioavailability of fluoride in the soil, soil amendment with dried
seaweed (DSW) led to a decrement of Ws-F from 81.7 ± 3.1 mg/kg up to 28.5 mg/kg whereas
the fermented seaweed (FSW) decreased Ws-F from 81.7 ± 3.1 mg/kg to 12 ± 1.3 mg/kg
following 5 % (w/w) amendments. But unlike DSW and FSW, seaweed-derived biochar (SB)
adsorbed fluoride at specific pH five (5) from 103.1 mg/kg to 91.2 ± 3.2 mg/kg whereas
hydroxyapatite activated seaweed-biochar (HSB) exhibited defluoridation capabilities at varies
pH (3 – 11) with a maximum Ws-F reduction from 103.1 mg/kg to 21.6 ± 2.1 mg/kg which is
close to the recommended limit of 16.4 mg/kg. The DSW and FSW defluoridation was based
on complexation reactions, alteration of soil properties, and increasing the soil-specific surface
area, but SB and HSB defluoridation was through chemisorption. Therefore, seaweed-derived
materials are capable of remediation of fluoride contaminated soils and the study recommends
further investigation on fluoride uptake by crops in pot and field experiments post-amendment
with seaweed derived materials
Mitochondrial DNA revealed a single stock structure of the Spotted sardinella Amblygaster sirm (Walbaum, 1792) (Teleostei; Clupeidae) in Tanzanian coastal waters
Get PDFA research article was submitted to Marine Biodiversity volume 53, 2023The Spotted sardinella Amblygaster sirm are small pelagic fish that are important protein source to coastal communities in the Indo-West Pacific. In this study, a cytochrome c oxidase subunit 1 (COI) gene of A. sirm from Tanzania was amplified to assess the species’ genetic structure and demographic history. All individuals collected were identified using both morphological examination and genetic barcoding as A. sirm. A total of 19 haplotypes were found in the dataset, with low overall nucleotide (π = 0.13 ± 0.001) and moderate haplotype diversities (h = 0.45 ± 0.07). AMOVA revealed a very low and non-significant genetic differentiation in the dataset (Fst = 0.002, Фst = −0.004, p > 0.05), indicating a lack of population structure. The minimum spanning haplotype network revealed additional evidence for the lack of population structure, which grouped all the sampled haplotypes into one cluster, regardless of their geographical regions. The Tajima’s D, Fu’s Fs tests, and mismatch distribution analyses supported a hypothesis of recent demographic expansion. The lack of population structure identified suggests that the fishery should be treated as a single-stock management unit, consistent with the existing management regime for the species in Mainland Tanzania that currently does not consider genetic structure in managing the fishery. The lack of population structure suggests that populations with low genetic diversity, such as Dar es Salaam, can rebuild by recruiting from other sites if regulations against unsustainable fishing are strictly enforced
Real-Time IoT-Based Air Quality Monitoring and Health Hazards Indicator System for Mines Regions: A Case Study of Bulyanhulu Gold Mine
Get PDFThis research article was published by International Journal of Computer Science and Mobile Computing Vol.12 Issue.7, July- 2023Air quality in mining regions is a significant concern due to the release of pollutants from mining
activities, posing health risks to nearby communities. However, limited information on air quality levels often
leads to neglect of this issue. Inhaling pollutants like PM2.5/PM10, CO, CO2, SO2, and NO2 can result in
chronic diseases such as respiratory issues, asthma, and cancer. To tackle this problem, a study suggests the
implementation of a real-time Internet of Things (IoT)-based air quality monitoring and health hazards
indicator system for mining regions. The proposed system utilizes a reliable wireless sensing system,
incorporating sensors like MQ7, MQ135, MQ136, MiCS4514, PMS7003, and DHT22, along with ESP8266,
STM32, ATmega328 microcontroller, LoRa shields, and the ThingSpeak IoT server. It ensures continuous
operation with a self-contained design, including a solar charger shield connected to a photovoltaic solar
panel and rechargeable battery. The smart sensing device continuously monitors air quality and uploads
real-time data to the cloud through a coordinator node. The collected data is processed to calculate the Air
Quality Index (AQI), which is analyzed to generate early warnings and indicate potential health hazards. The
results are accessible through a web-based dashboard for easy visualization. This system simplifies
monitoring and provides accurate pollutant data. It supports environmental stakeholders by aggregating and
analyzing air quality data, generating reports, and facilitating public access to air quality information.
Additionally, it helps identify health hazards, enabling informed decision-making, policy formulation, and
mitigation strategies
Development of an interactive mobile application for information sharing between sccult, member cooperatives (saccos), and other stakeholders
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 TechnologyThe use of mobile devices and their affiliated software has brought about a very immense
change in communication. From a different angle, marketing of goods and services for business
entities has been made easier and better. However, it has been discovered that, to know about
a specific entity one would need to have prior knowledge about it. This makes it hard for
unknown entities to become reached by potential buyers. This is the case for SACCOS and
SCCULT in Tanzania. The two become invisible to the consumer community due to their
infamous nature, making their marketing difficult and hence, stunting their growth. Savings
and Credit Cooperative Unions (SACCOS) are financial groups that provide their members
with different financial services, including loans, savings, and investments. By lending capital
to Small and Medium Enterprises, SACCOS have been a source of close to 94.7%
employments of their members. It as well contributes up to 40% of the national Gross Domestic
Product (GDP). However, only less than 10% of the national population is beneficiary of the
services offered by SACCOS in Tanzania. The purpose of this study was to bring to attention
that most individuals do not engage with SACCOS and enjoy their easy and smooth services
because they lack information. The study proved that with enough information and engagement
of the SACCOS to society, many individuals could join SACCOS and enjoy their benefits. A
mixed research method was used to gather information on the society’s awareness of SACCOS,
their knowledge, and usage of social media, and whether they have ever encountered news
about SACCOS in their social media exploration. It was discovered that more than 70% of
individuals have poor or no knowledge at all about SACCOS. The study discovered that, due
to a large number of content contexts in social media, SACCOS are not easily found in such a
pool of information. This project resulted in the development of an interactive mobile
application for information sharing between the Savings and Credit Cooperatives Union
League of Tanzania (SCCULT), their member cooperatives (SACCOS), and other stakeholders
including the Tanzanian society mass. This is a mobile application dedicated to sharing news
with society in a broader and more relevant way. Allowing individuals to have ease of access
to SACCOS’s basic information enough to help them build interest in joining them
Effect of groundwater residence time on geogenic fluoride release into groundwater in the Mt. Meru slope area, Tanzania, the Great Rift Valley, East Africa
No full textThis research articles was published in Journal of Contaminant Hydrology Volume 254,2023People living in the Great Rift Valley in East Africa suffer from fluorosis resulting from their consumption of groundwater. This paper shows that geogenic fluoride contamination in a natural water system has changed in the last two decades in the Mt. Meru slope area of northern Tanzania based on water quality, dating of the residence time, and stable isotopes of groundwater. The results demonstrate that 1) the average recharge altitude of groundwater with a high geogenic fluoride concentration is estimated to range from 1900 m to 3000 m on the southern slope of Mt. Meru, and the fluoride concentration tends to increase with an increase in the recharge altitude, 2) the fluoride concentration increases with increasing groundwater residence time for groundwater with a residence time of 20 years or longer, suggesting that water-rock interaction processes (weathering, dissolution, and ion exchange), which depend on the contact time between the volcanic aquifer and groundwater, have predominated for approximately 20 years or longer, and 3) the mixing of aerobic young water and old groundwater has been active for approximately 20 years, and the fluoride concentration is increasing in some shallower well waters. The mixing of fluoride-contaminated groundwater with aerobic water infiltrating the aquifer through pumping groundwater in the last two decades may increase the spread of groundwater contaminated with fluoride due to increased water demand caused by rapid population growth, and urbanization, industrial growth, and the expansion of irrigated agriculture
Air pollution exposure and non-communicable respiratory diseases among fish vendors in Bagamoyo and Kunduchi fish markets in Tanzania
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirement for the Degree of Master of Science in Public Health Research of the Nelson Mandela African Institution of Science and Technology.Approximately 2.6 billion people in the world use polluting fuels in cooking. Small-scale fish
vendors in Bagamoyo and Kunduchi fish markets rely on use of firewood in frying fish for business
purposes. Unfortunately, this results in higher levels of air pollutants as an occupational exposure.
The study assessed the magnitude of air pollution and related impacts on lung function among
small-scale fish vendors along coastal area of Tanzania. The study was a cross-sectional
descriptive study, conducted in Bagamoyo and Kunduchi fish markets. Air pollution levels and
composition were measured. EasyOne spirometer was used to test for lung function and a
standardized questionnaire was used to assess respiratory symptoms among small-scale fish
vendors. Data were analyzed using STATA Version 17. Results shows that the average hourly
concentration levels of Particulate matter (PM1, PM2.5, PM10), and Carbon monoxide exposure
during fish frying were 653.6 (±206.3 SD) µg/m3
, 748.5 (±200.6 SD) µg/m3
, 798.7 (±181.7 SD)
µg/m3
and 62.6 (±12.3 SD) ppm respectively which is higher than the WHO recommended limits.
About 32.04% of participants were categorized as having chronic obstructed pulmonary disease
which was associated with coughing, wheezing, sputum production and breathlessness among the
participants. Findings suggest that three out of ten participants had COPD and the major
environmental air pollutants concentration levels were too high, suggesting occupational exposure
to biomass smoke may be a major risk factor. This calls for effective approaches to reduce
exposure and prevent known acute and chronic respiratory diseases that are associated with such
exposure to air pollutants
An Internet of Things Based system for Road Surface Condition Assessment Using Machine Learning
No full textThis research article was published by IEEE Xplore 2023,
,Road surface condition assessment is crucial for maintaining road safety and preserving road infrastructure. However, techniques for assessing road conditions employed in Tanzania are manual and labor-intensive, leading to slow and ineffective repair practices. To address these challenges, this project developed an Internet of Things-based system for Road Surface Condition Assessment using Machine Learning. The system collects real-time data on road surface conditions using camera and gyroscope sensors; processes the data using machine learning algorithms to detect defects on the road surface. The data is used for decision support by the maintenance authorities to ease their process by automation of road condition surveys. The effectiveness of the developed system was evaluated through a qualitative study that collected data on road condition assessment practices in Tanzania. The results indicate that the proposed system provides a more efficient, cost-effective, and comprehensive method for assessing road conditions in Tanzania. The study found that the proposed system facilitated efficient road maintenance. This project highlights the potential of IoT and machine learning in addressing road safety and labor requirement challenges faced by developing countries in the field of infrastructure management, it also offers a valuable contribution to the field of transportation and engineering
Bacterial communities structure in constructed wetlands for municipal and industrial wastewater treatment in Tanzania
Get PDFThis research article was published by Water Practice & Technology Vol 00 No 0,2023Bacteria are the largest and most essential microorganisms in wastewater treatment systems. Despite the vital role bacteria
play in enhancing wastewater treatment, its community structure and diversity remain poorly known. This study elucidated bac-
terial diversity and community structure in constructed wetlands (CWs) for municipal and industrial wastewater treatment using
a culture-independent approach. Analysis of physicochemical parameters and Illumina high-throughput sequencing of V3 and
V4 hypervariable regions of 16S rRNA gene bacterial community was performed. The results showed that the Proteobacteria
were dominant (48.66%) phyla across all CWs. The Gammaproteobacteria class (27.67%), family Comamonadaceae (35.79)
and Genus Flavobacterium (4.35%) were dominant across studied CWs. Bacterial abundance increased from the inlet to the
outlet, with CWs having a higher abundance around the outlet, showing a good performance. The Shannon–Wiener index
showed the highest species diversity (H ¼ 1.45) in Banana Investment Limited CWs treating industrial wastewater. This study
found significant bacterial diversity across studied CWs, with higher abundance and diversity at the outlet indicating better per-
formance than those with low abundance and diversity at the outlet. We recommend a longitudinal investigation at each CWs
section to confirm and establish the role of bacterial diversity on the performance pattern of CWs
Development of early warning system for human wildlife conflict using deep learning, iot and sms
Get PDFA Project Report Submitted in Partial Fulfilment of the Requirements for the Degree of
Master of Science in Embedded and Mobile Systems of the Nelson Mandela African
Institution of Science and TechnologyHuman-wildlife conflict is a significant challenge to communities living in areas close to
wildlife game parks and reserves. It is more evident in the United Republic of Tanzania whose
economy depends on agriculture and wildlife tourism as a significant source of income for her
citizens and foreign exchange respectively. The proposed system is a low-power and low-cost
early-warning system using deep learning, Internet of Things (IoT) and Short Message Service
(SMS) to support human-wildlife conflict response teams in mitigating these problems. The
proposed system comprises three basic units: sensing unit, processing unit, and alerting unit.
The sensing unit consists of a Global Positioning System (GPS) module, a passive infrared
(PIR) sensor, and a Raspberry Pi camera. The PIR sensor module detects animal nearby using
its heat signature, the GPS collects and records the current system location while the Raspberry
pi camera takes an image after the PIR sensor has detected the animal nearby using its heat
signature. The processing unit with the main unit uses a Raspberry microcomputer to perform
image inferencing using the “you look only once” (YOLO) algorithm and data processing. The
last unit is an alerting unit that uses Global System for Mobile Communications module to send
an alerting SMS message to the community response team leader and the human-wildlife
conflict response team whenever wild animals are detected near the park’s border. Therefore,
the system detects, identifies, and reports wild animals detected using SMS. General Packet
Radio Service cellular network provides internet connectivity for the purpose of data collection
to enable monitoring and storage in the cloud. An online visualization system was developed
using google maps to show the location of wildlife detected by the camera trap. The park
rangers track the wildlife online to acquire important information before the wildlife wanders
out of the park. This system was developed using the open-source Raspberry pi which is cost-
effective even for low-income communities who are targeted by the system