Knowledge of cervical tuberculosis lymphadenitis and its treatment in pastoral communities of the Afar region, Ethiopia

<p>Abstract</p> <p>Background</p> <p>Infection with <it>Mycobacterium bovis </it>(Mb) predominantly causes cervical TB lymphadenitis (TBL). Raw milk is considered the main source of Mb infection and raw milk is a major food source for Afar pastoralists. The aim of this study was to assess Afar pastoralists' knowledge concerning cervical TBL and its treatment.</p> <p>Methods</p> <p>A community-based cross-sectional survey involving 818 interviewees was conducted in two districts of the Afar Region, Ethiopia. In addition, two focus group discussions (FGDs) were conducted in each of the study areas, one with men and the other with women.</p> <p>Results</p> <p>Of the 818 interviewees [357 (43.6%) females and 461 (56.4%) males], 742 (90.7%) reported that they had knowledge of cervical TBL, mentioning that swelling(s) on the neck resulting in a lesion and scar are common symptoms. However, only 11 (1.5%) individuals mentioned that bacteria or germs are the causative agents of TBL. Three interviewees and a male discussant mentioned drinking raw milk as the cause of TBL. A considerable proportion (34.2%) of the interviewees and almost all the discussants suggested herbal medicine as an effective treatment. Male study participants were 1.82 times more likely to have overall knowledge of TBL than female study participants (adjusted OR, 1.82; 95% CI, 1.32 to 2.51, p < 0.001).</p> <p>Conclusion</p> <p>The pastoral community members in the study areas had little biomedical knowledge of the cause, the source of infection and the transmission route of cervical TBL. Furthermore, most community members believed that herbal medicines are the most effective treatment for TBL. Therefore, TB control programs in the Afar Region require the incorporation of public health education introducing current biomedical knowledge of the disease. In addition, further studies are important to elucidate which medicinal plants are used by Afar pastoralists to treat TBL.</p

Diversity of Mycobacterium tuberculosis genotypes circulating in Ndola, Zambia

<p>Abstract</p> <p>Background</p> <p>Tuberculosis (TB) is one of the major public health problems in Zambia. However, information about lineages of <it>M. tuberculosis </it>complex (MTBC) isolates useful for epidemiology investigations is unknown. In this study, we investigated the diversity of MTBC isolates from Ndola, a typical Zambian urbanized city with a documented high HIV prevalence.</p> <p>Methods</p> <p>This was part of a prospective cohort study in subjects with sputum smear-positive pulmonary TB. Spoligotyping was used to genotype the MTBC isolates and establish the circulating lineages. The 15-locus Mycobacterial Interspersed Repetitive Units - Variable Number Tandem Repeats (MIRU-VNTR) typing was used to study recent transmission.</p> <p>Results</p> <p>A total of 98 different spoligotypes were identified among 273 MTBC isolates. The majority (64.8%) of the isolates belonged to 9 known families, while 96 (35.2%) of the isolates were orphans. While LAM (41.8%) was the largest spoligotype family observed, most of the isolates (87.7%) belonging to the SAF1 family, with a significant portion coming from the T (13.6%), and X (5.9%) families. A few isolates (3.6%) belonged to the CAS, EAI, H, S, X1-LAM9 or U families. MIRU-VNTR typing was highly discriminatory (h = 0.988) among the 156 isolates tested in our sample, and increased the discrimination among 82 SAF1 isolates from 6 to 46 distinct patterns. In addition, 3.2% (5/156) of cases with available MIRU-VNTR results harbored more than one MTBC strain.</p> <p>Conclusions</p> <p>Our findings show a limited diversity of MTBC in Ndola with a high clustering rate (37.7%), which indicates that recent transmission plays an appreciable role in the dynamics of TB disease in this setting. This conclusion emphasizes the importance of early diagnosis and timely treatment. The results also confirm that MIRU-VNTR typing is suitable for studying the molecular epidemiology of TB in Ndola.</p

The impact of migration on tuberculosis epidemiology and control in high-income countries: a review.

Tuberculosis (TB) causes significant morbidity and mortality in high-income countries with foreign-born individuals bearing a disproportionate burden of the overall TB case burden in these countries. In this review of tuberculosis and migration we discuss the impact of migration on the epidemiology of TB in low burden countries, describe the various screening strategies to address this issue, review the yield and cost-effectiveness of these programs and describe the gaps in knowledge as well as possible future solutions.The reasons for the TB burden in the migrant population are likely to be the reactivation of remotely-acquired latent tuberculosis infection (LTBI) following migration from low/intermediate-income high TB burden settings to high-income, low TB burden countries.TB control in high-income countries has historically focused on the early identification and treatment of active TB with accompanying contact-tracing. In the face of the TB case-load in migrant populations, however, there is ongoing discussion about how best to identify TB in migrant populations. In general, countries have generally focused on two methods: identification of active TB (either at/post-arrival or increasingly pre-arrival in countries of origin) and secondly, conditionally supported by WHO guidance, through identifying LTBI in migrants from high TB burden countries. Although health-economic analyses have shown that TB control in high income settings would benefit from providing targeted LTBI screening and treatment to certain migrants from high TB burden countries, implementation issues and barriers such as sub-optimal treatment completion will need to be addressed to ensure program efficacy

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Photovoltaic Power Generation Forecasting for Regional Assessment Using Machine Learning

Solar energy currently plays a significant role in supplying clean and renewable electric energy worldwide. Harnessing solar energy through PV plants requires problems such as site selection to be solved, for which long-term solar resource assessment and photovoltaic energy forecasting are fundamental issues. This paper proposes a fast-track methodology to address these two critical requirements when exploring a vast area to locate, in a first approximation, potential sites to build PV plants. This methodology retrieves solar radiation and temperature data from free access databases for the arbitrary division of the region of interest into land cells. Data clustering and probability techniques were then used to obtain the mean daily solar radiation per month per cell, and cells are clustered by radiation level into regions with similar solar resources, mapped monthly. Simultaneously, temperature probabilities are determined per cell and mapped. Then, PV energy is calculated, including heat losses. Finally, PV energy forecasting is accomplished by constructing the P50 and P95 estimations of the mean yearly PV energy. A case study in Mexico fully demonstrates the methodology using hourly data from 2000 to 2020 from NSRDB. The proposed methodology is validated by comparison with actual PV plant generation throughout the country