VoIP音声信号における雑音とネットワークによる音声の歪みの影響に関する研究

兵庫県立大学大学院博士（応用情報科学）2023doctoral thesi

Regional Differences in Intervention Coverage and Health System Strength in Tanzania.

Assessments of subnational progress and performance coverage within countries should be an integral part of health sector reviews, using recent data from multiple sources on health system strength and coverage. As part of the midterm review of the national health sector strategic plan of Tanzania mainland, summary measures of health system strength and coverage of interventions were developed for all 21 regions, focusing on the priority indicators of the national plan. Household surveys, health facility data and administrative databases were used to compute the regional scores. Regional Millennium Development Goal (MDG) intervention coverage, based on 19 indicators, ranged from 47% in Shinyanga in the northwest to 71% in Dar es Salaam region. Regions in the eastern half of the country have higher coverage than in the western half of mainland. The MDG coverage score is strongly positively correlated with health systems strength (r = 0.84). Controlling for socioeconomic status in a multivariate analysis has no impact on the association between the MDG coverage score and health system strength. During 1991-2010 intervention coverage improved considerably in all regions, but the absolute gap between the regions did not change during the past two decades, with a gap of 22% between the top and bottom three regions. The assessment of regional progress and performance in 21 regions of mainland Tanzania showed considerable inequalities in coverage and health system strength and allowed the identification of high and low-performing regions. Using summary measures derived from administrative, health facility and survey data, a subnational picture of progress and performance can be obtained for use in regular health sector reviews

Detection of Rift Valley Fever Virus Interepidemic Activity in Lower Moshi area of Kilimanjaro Region, North Eastern Tanzania: A Community Survey

This research article published by Research square, 2021Background: Rift Valley fever virus (RVFV) is a zoonotic arbovirus of public health impact infecting livestock, wildlife, and humans mainly in Africa and other parts of the world. Despite its public health importance, mechanisms of RVFV maintenance during inter-epidemic (IEPS) periods and potentially spread to new areas remain unclear.We aimed to comparatively examine exposure to RVFV and RVFV infection among humans, goats and mosquitoes in an agro-pastoral community in Lower Moshi area of Moshi rural district. Results:Results show that the male gender was related to RVFV seropositivity (χ2 = 5.351; p=0.030). Being 50 years and above was related to seropositivity (χ2=14.430; p=0.006) whereas bed net use, larger numbers of persons living in the same house (>7 persons) and RVFV seropositivity in goats were related to higher seropositivity to RVFV among humans (χ2=6.003; p=0.021, χ2=23.213; p=0.000 and 27.053; p=0.000), respectively.RVFV antibody concentrations were only marginally higher in humans without statistically significant difference [t (112) =0.526; p=0.60)]. By the use of RT-qPCR, goats exhibited the highest RVFV infection rate of 4.1%, followed by humans (2.6%), Aedes spp(2.3%), and Culex spp(1.5%). Conclusions: In the absence of RVFV infection data in areas nearby the study site, our findings suggest Lower Moshi area as a potential hotspot for RVF, posing the danger of being a source of RVFV spread to other areas. Goats had the highest infection rate, suggesting goats as important hosts in the virus maintenance during IEPs. We recommend the design and implementation of strategies that will warrant effective active surveillance of RVF through the identification of RVF hotspots for targeted control of RVF

Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data

Recent malaria control efforts in mainland Tanzania have led to progressive changes in the prevalence of malaria infection in children, from 18.1% (2008) to 7.3% (2017). As the landscape of malaria transmission changes, a sub-national stratification becomes crucial for optimized cost-effective implementation of interventions. This paper describes the processes, data and outputs of the approach used to produce a simplified, pragmatic malaria risk stratification of 184 councils in mainland Tanzania.; Assemblies of annual parasite incidence and fever test positivity rate for the period 2016-2017 as well as confirmed malaria incidence and malaria positivity in pregnant women for the period 2015-2017 were obtained from routine district health information software. In addition, parasite prevalence in school children (PfPR; 5to16; ) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014-2015 and 2017. The PfPR; 5to16; served as a guide to set appropriate cut-offs for the other indicators. For each indicator, the maximum value from the past 3 years was used to allocate councils to one of four risk groups: very low (< 1%PfPR; 5to16; ), low (1- < 5%PfPR; 5to16; ), moderate (5- < 30%PfPR; 5to16; ) and high (≥ 30%PfPR; 5to16; ). Scores were assigned to each risk group per indicator per council and the total score was used to determine the overall risk strata of all councils.; Out of 184 councils, 28 were in the very low stratum (12% of the population), 34 in the low stratum (28% of population), 49 in the moderate stratum (23% of population) and 73 in the high stratum (37% of population). Geographically, most of the councils in the low and very low strata were situated in the central corridor running from the north-east to south-west parts of the country, whilst the areas in the moderate to high strata were situated in the north-west and south-east regions.; A stratification approach based on multiple routine and survey malaria information was developed. This pragmatic approach can be rapidly reproduced without the use of sophisticated statistical methods, hence, lies within the scope of national malaria programmes across Africa

Improving quality of medical certification of causes of death in health facilities in Tanzania 2014-2019

BACKGROUND: Monitoring medically certified causes of death is essential to shape national health policies, track progress to Sustainable Development Goals, and gauge responses to epidemic and pandemic disease. The combination of electronic health information systems with new methods for data quality monitoring can facilitate quality assessments and help target quality improvement. Since 2015, Tanzania has been upgrading its Civil Registration and Vital Statistics system including efforts to improve the availability and quality of mortality data. METHODS: We used a computer application (ANACONDA v4.01) to assess the quality of medical certification of cause of death (MCCD) and ICD-10 coding for the underlying cause of death for 155,461 deaths from health facilities from 2014 to 2018. From 2018 to 2019, we continued quality analysis for 2690 deaths in one large administrative region 9 months before, and 9 months following MCCD quality improvement interventions. Interventions addressed governance, training, process, and practice. We assessed changes in the levels, distributions, and nature of unusable and insufficiently specified codes, and how these influenced estimates of the leading causes of death. RESULTS: 9.7% of expected annual deaths in Tanzania obtained a medically certified cause of death. Of these, 52% of MCCD ICD-10 codes were usable for health policy and planning, with no significant improvement over 5 years. Of certified deaths, 25% had unusable codes, 17% had insufficiently specified codes, and 6% were undetermined causes. Comparing the before and after intervention periods in one Region, codes usable for public health policy purposes improved from 48 to 65% within 1 year and the resulting distortions in the top twenty cause-specific mortality fractions due to unusable causes reduced from 27.4 to 13.5%. CONCLUSION: Data from less than 5% of annual deaths in Tanzania are usable for informing policy. For deaths with medical certification, errors were prevalent in almost half. This constrains capacity to monitor the 15 SDG indicators that require cause-specific mortality. Sustainable quality assurance mechanisms and interventions can result in rapid improvements in the quality of medically certified causes of death. ANACONDA provides an effective means for evaluation of such changes and helps target interventions to remaining weaknesses

An examination of the capital structure decisions by companies quoted on the Dar es Salaam Stock Exchange.

Submitted in Partial Fulfillment of the Requirements for the Degree of Master of CommerceThis study was carried out in Tanzania. The study was intended to examine the levels of debt and equity employed by companies quoted on the Dar es Salaam Stock Exchange (OSE) in financing their businesses. The study also aimed at identifying the significant factors that influence the capital structure and further to examine the financial managers' opinions on the factors they perceive important in influencing the capital structure. The study focused on 9 selected non-financial companies quoted on the (OSE). The data was collected for 10 years beginning 2000 to 2009 and was obtained from the companies' financial reports and from questionnaires that were mailed to the (CFOs) of all the 9 companies. The most important theories that have guided this study are pecking order theory, agency cost theory and trade-off theory. By using descriptive analysis, it has been found that companies quoted on the (OSE) are on average moderately levered as they prefer relatively more equity to debt. By using regression analysis, the empirical results show that the significant factors influencing the capital structure of companies quoted on the (OSE) are; industry class, company profitability, company size, non-debt tax shields and growth opportunities. Contrary to the outcome of prior studies in developing countries, this study finds that asset tangibility, earnings volatility and effective tax rate are positively related with capital structure. The results of regression are consistent with the opinions of the CFOs except for assets tangibility, earnings volatility and effective tax rate which are perceived by (CFOs) as important factors while the regression analysis shows them as not influential factors on capital structure by companies quoted on the (OSE)The possible explanation for these differences may be that company officials perceive some of the factors as important while in reality they are not. This study makes several contributions to the body of knowledge as well as providing insights to academicians. The study further reveals that there is no single theory that simultaneously predicts the full set of the reliable factors; this warrants further development of the capital structure theories. Finally, the researcher concludes that capital structure decisions varies from country to country and even from industry to industry and should be dealt as such

MiniatureVQNet: A Light-Weight Deep Neural Network for Non-Intrusive Evaluation of VoIP Speech Quality

In IP audio systems, audio quality is degraded by environmental noise, poor network quality, and encoding–decoding algorithms. Therefore, there is a need for a continuous automatic quality evaluation of the transmitted audio. Speech quality monitoring in VoIP systems enables autonomous system adaptation. Furthermore, there are diverse IP audio transmitters and receivers, from high-performance computers and mobile phones to low-memory and low-computing-capacity embedded systems. This paper proposes MiniatureVQNet, a single-ended speech quality evaluation method for VoIP audio applications based on a lightweight deep neural network (DNN) model. The proposed model can predict the audio quality independent of the source of degradation, whether noise or network, and is light enough to run in embedded systems. Two variations of the proposed MiniatureVQNet model were evaluated: a MiniatureVQNet model trained on a dataset that contains environmental noise only, referred to as MiniatureVQNet–Noise, and a second model trained on both noise and network distortions, referred to as MiniatureVQNet–Noise–Network. The proposed MiniatureVQNet model outperforms the traditional P.563 method in terms of accuracy on all tested network conditions and environmental noise parameters. The mean squared error (MSE) of the models compared to the PESQ score for ITU-T P.563, MiniatureVQNet-Noise, and MiniatureVQNet–Noise–Network was 2.19, 0.34, and 0.21, respectively. The performance of both the MiniatureVQNet–Noise–Network and MiniatureVQNet-Noise model depends on the noise type for an SNR greater than 0 dB and less than 10 dB. In addition, training on a noise–network-distorted speech dataset improves the model prediction accuracy in all VoIP environment distortions compared to training the model on a noise-only dataset

A study of the Effect of Noise and Network Distortions in VoIP Speech Signals

202

Perceived Usefulness, Competency, and Associated Factors in Using District Health Information System Data Among District Health Managers in Tanzania: Cross-sectional Study

BackgroundTanzania introduced District Health Information Software (version 2; DHIS2) in 2013 to support existing health management information systems and to improve data quality and use. However, to achieve these objectives, it is imperative to build human resource capabilities to address the challenges of new technologies, especially in resource-constrained countries. ObjectiveThis study aimed to determine the perceived usefulness, competency, and associated factors in using DHIS2 data among district health managers (DHMs) in Tanzania. MethodsThis descriptive cross-sectional study used a quantitative approach, which involved using a self-administered web-based questionnaire. This study was conducted between April and September 2019. We included all core and co-opted members of the council or district health management teams (DHMTs) from all 186 districts in the country. Frequency and bivariate analyses were conducted, and the differences among categories were measured by using a chi-square test. P values of <.05 were considered significant. ResultsA total of 2667 (77.96%) of the expected 3421 DHMs responded, of which 2598 (97.41%) consented and completed the questionnaires. Overall, the DHMs were satisfied with DHIS2 (2074/2596, 79.83%) because of workload reduction (2123/2598, 81.72%), the ease of learning (1953/2598, 75.17%), and enhanced data use (2239/2598, 86.18%). Although only half of the managers had user accounts (1380/2598, 53.12%) and were trained on DHIS2 data analysis (1237/2598, 47.61%), most claimed to have average to advanced skills in data validation (1774/2598, 68.28%), data visualization (1563/2598, 60.16%), and DHIS2 data use (1321/2598, 50.85%). The biggest challenges facing DHMs included the use of a paper-based system as the primary data source (1890/2598, 72.75%) and slow internet speed (1552/2598, 59.74%). Core members were more confident in using DHIS2 compared with other members (P=.004), whereas program coordinators were found to receive more training on data analysis and use (P=.001) and were more confident in using DHIS2 data compared with other DHMT members (P=.001). ConclusionsThis study showed that DHMs have appreciable competencies in using the DHIS2 and its data. However, their skill levels have not been commensurate with the duration of DHIS2 use. This study recommends improvements in the access to and use of DHIS2 data. More training on data use is required and should involve using cost-effective approaches to include both the core and noncore members of the DHMTs. Moreover, enhancing the culture and capacity of data use will ensure the better management and accountability of health system performance