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Anemia is a nutritional disorder that affects mostly children below 2 years and is mainly contributed by iron deficiency. Moringa oleifera leaves are rich in iron and other essential nutrients necessary for iron metabolism. We investigated the effect of M. oleifera leaf powder supplementation on reducing anemia among children below 2 years. A community‐based interventional study was conducted that enrolled 95 anemic children who were followed for 6 months. The intervention communities received M. oleifera leaf powder and nutrition education, while control communities only received nutrition education. Changes on mean hemoglobin (Hb) concentration and anemia prevalence were compared between the two groups using t test and proportional test where appropriate. At baseline, the mean Hb concentrations of control and intervention groups were 7.9 g/dl (SD = 1.3) and 8.3 g/dl (SD = 1.6) g/L, respectively (p‐value = 0.0943). After 6 months, anemia prevalence significantly decreased in the intervention group by 53.6% (100%–46.4%; p

Background Health Management Information System (HMIS) is a set of data regularly collected at health care facilities to meet the needs of statistics on health services. This study aimed to determine the utilisation of HMIS data and factors influencing the health system’s performance at the district and primary health care facility levels in Tanzania. Methods This cross-sectional study was carried out in 11 districts and involved 115 health care facilities in Tanzania. Data were collected using a semi-structured questionnaire administered to health workers at facility and district levels and documented using an observational checklist. Thematic content analysis approach was used to synthesise and triangulate the responses and observations to extract essential information. Results A total of 93 healthcare facility workers and 13 district officials were interviewed. About two-thirds (60%) of the facility respondents reported using the HMIS data, while only five out of 13 district respondents (38.5%) reported analysing HMIS data routinely. The HMIS data were mainly used for comparing performance in terms of services coverage (53%), monitoring of disease trends over time (50%), and providing evidence for community health education and promotion programmes (55%). The majority (41.4%) of the facility’s personnel had not received any training on data management related to HMIS during the past 12 months prior to the survey. Less than half (42%) of the health facilities had received supervisory visits from the district office 3 months before this assessment. Nine district respondents (69.2%) reported systematically receiving feedback on the quality of their reports monthly and quarterly from higher authorities. Patient load was described to affect staff performance on data collection and management frequently. Conclusion Inadequate analysis and poor data utilisation practices were common in most districts and health facilities in Tanzania. Inadequate human and financial resources, lack of incentives and supervision, and lack of standard operating procedures on data management were the significant challenges affecting the HMIS performance in Tanzania.

Background Antimicrobial resistance due to production of extended-spectrum β-lactamase (ESBL) by Enterobacteriaceae is a global health problem contributing to increased morbidity and mortality particularly in resource-constrained countries. We examined in the current study the prevalence of extended spectrum β-lactamase producing Enterobacteriaceae (ESBL-E) in community patients in Blantyre, Malawi. Methods This was a cross sectional study conducted between March and September 2020 at selected outpatient health facilities in Blantyre, Malawi. Clinical samples were first screened for ESBL-E using CHROMagar™ ESBL medium and later confirmed by a combination disk test method (CDT). The isolates were identified to species level using a commercially acquired biochemical substrate strips (Microbact™ GNB, Oxoid). Descriptive summary statistics were generated as frequencies and proportions. Chi square or Fishers Exact tests and student’s t-test were used where appropriate. Association between variables was determined by logistic regression analysis. Results were presented as odds ratio and 95% confidence interval. A p-value ≤ 0.05 was regarded as statistically significant. Results A total of 199 rectal swabs and 101 urine samples from 300 outpatient adults were screened for ESBL-E. Of these, seventy three (24.33%; 95%, CI = 19.45–29.22%) gave positive culture. Prevalence of community acquired ESBL-E was 16.67% (50/300, 95% CI = 12.43–20.91%). The most common ESBL-E species isolated were Escherichia coli (66%). Community prevalence of ESBL-E was higher in male 56% (28/50) compared to female 44% (22/50) patients. Prevalence of ESBL-E was higher in community patients who lacked history of surgery 88% (44/50) and prior history of antibiotic use in the last three months 80% (40/50) compared to those with same characteristics. All community patients with isolated ESBL-E had no history of admission in the last three months and neither demographic characteristics nor clinical characteristics of participants showed any degree of association with the carriage of ESBL-E. Conclusion Our findings revealed moderate presence of ESBL-E phenotypes in a community patients who lacked history of hospital admissions in the past three months an indication of community acquisition of ESBL-E in Blantyre, Malawi. Low prevalence of ESBL-E in the community settings in Blantyre can be maintained if strong infection and antimicrobial use control strategies are to be implemented.

Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. These results can inform both policy decisions and downstream malaria analyses.

Background Human immunodeficiency virus (HIV) remains a public health priority in Latin America. While the burden of HIV is historically concentrated in urban areas and high-risk groups, subnational estimates that cover multiple countries and years are missing. This paucity is partially due to incomplete vital registration (VR) systems and statistical challenges related to estimating mortality rates in areas with low numbers of HIV deaths. In this analysis, we address this gap and provide novel estimates of the HIV mortality rate and the number of HIV deaths by age group, sex, and municipality in Brazil, Colombia, Costa Rica, Ecuador, Guatemala, and Mexico. Methods We performed an ecological study using VR data ranging from 2000 to 2017, dependent on individual country data availability. We modeled HIV mortality using a Bayesian spatially explicit mixed-effects regression model that incorporates prior information on VR completeness. We calibrated our results to the Global Burden of Disease Study 2017. Results All countries displayed over a 40-fold difference in HIV mortality between municipalities with the highest and lowest age-standardized HIV mortality rate in the last year of study for men, and over a 20-fold difference for women. Despite decreases in national HIV mortality in all countries—apart from Ecuador—across the period of study, we found broad variation in relative changes in HIV mortality at the municipality level and increasing relative inequality over time in all countries. In all six countries included in this analysis, 50% or more HIV deaths were concentrated in fewer than 10% of municipalities in the latest year of study. In addition, national age patterns reflected shifts in mortality to older age groups—the median age group among decedents ranged from 30 to 45 years of age at the municipality level in Brazil, Colombia, and Mexico in 2017. Conclusions Our subnational estimates of HIV mortality revealed significant spatial variation and diverging local trends in HIV mortality over time and by age. This analysis provides a framework for incorporating data and uncertainty from incomplete VR systems and can help guide more geographically precise public health intervention to support HIV-related care and reduce HIV-related deaths.

Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. The primary driving factors behind these findings are most likely strong cultural and social messaging around the importance of net use, low physical net durability, and a mixture of inherent commodity distribution challenges and less-than-optimal net allocation policies, respectively. These results can inform both policy decisions and downstream malaria analyses., Insecticide treated nets (ITNs) are an important part of malaria control in Africa and WHO targets aim for 80% coverage. This study estimates the spatio-temporal access and use of ITNs in Africa from 2000-2020, and shows that both metrics have improved over time but access remains below WHO targets.

Background Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use; its influence on malaria burden varies through space and time. Methods This study uses data from 232 efficacy trials comprised of 86,776 infected individuals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. Results The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3–75.8), 70.1% (43.6–76.0) and 71.8% (46.9–76.4) for the 1991–2000, 2006–2010, and 2016–2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9–74.9) for 1991–2000 and 55.5% (27.1–73.4) for 2011–2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. Conclusions This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries’ treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.

BackgroundResearch integrity and research fairness have gained considerable momentum in the past decade and have direct implications for global health epidemiology. Research integrity and research fairness principles should be equally nurtured to produce high-quality impactful research—but bridging the two can lead to practical and ethical dilemmas. In order to provide practical guidance to researchers and epidemiologist, we set out to develop good epidemiological practice guidelines specifically for global health epidemiology, targeted at stakeholders involved in the commissioning, conduct, appraisal and publication of global health research.MethodsWe developed preliminary guidelines based on targeted online searches on existing best practices for epidemiological studies and sought to align these with key elements of global health research and research fairness. We validated these guidelines through a Delphi consultation study, to reach a consensus among a wide representation of stakeholders.ResultsA total of 45 experts provided input on the first round of e-Delphi consultation and 40 in the second. Respondents covered a range of organisations (including for example academia, ministries, NGOs, research funders, technical agencies) involved in epidemiological studies from countries around the world (Europe: 19; Africa: 10; North America: 7; Asia: 5; South-America: 3 Australia: 1). A selection of eight experts were invited for a face-to-face meeting. The final guidelines consist of a set of 6 standards and 42 accompanying criteria including study preparation, protocol development, data collection, data management, data analysis, dissemination and communication.ConclusionWhile guidelines will not by themselves guard global health from questionable and unfair research practices, they are certainly part of a concerted effort to ensure not only mutual accountability between individual researchers, their institutions and their funders but most importantly their joint accountability towards the communities they study and society at large.

Background: Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low and middle-income countries. This study was carried out to determine the patterns, trends, and causes of non-communicable disease mortality in hospitals of Tanzania from 2006-2015.Methods: This retrospective study involved primary, secondary, tertiary, and specialized hospitals in Tanzania. Death statistics were extracted from inpatient department registers, death registers, and International Classification of Diseases (ICD) report forms. Variables collected were deceased’s age, sex, cause and date of death. The ICD-10 coding system was used to assign each death to its underlying cause. Data were analysed using STATA version 14. Results: A total of 247,976 deaths were reported during the 10 years (2006–2015) in 39 hospitals. Of the total deaths, 67,711 (27.3%) were due to non-communicable diseases (NCD) and injuries. Cardio-circulatory diseases (31.9%), cancers (18.6%), chronic respiratory diseases (18.4%), and injuries (17.9%) accounted for the largest proportion (86.8%) of deaths due to NCDs. The majority (57.6%) of deaths due to NCD occurred among males. Overall, the total deaths from NCDs increased by 153.3% from 4,298 in 2006 to 10,886 in 2015. The age group 15-59 years (53.4%) was the most affected category. The overall 10-year annual age-standardized mortality rate (ASMR) for all NCDs and injuries was 235.2 per 100,0000 population. It was higher for males (287.2/100,000) than for females (186.7/100,000). The annual ASMR increased from 11.9 in 2006 to 36.5 per 100,000 populations in 2015. Most of the NCD deaths occurred in the secondary (40.0%) and primary level hospitals (27.8%). There were variations in the type of non-communicable diseases by geographical distributions. Conclusions: There was a substantial increase in ASMR due to NCDs and injuries in Tanzania from 2006 to 2015. Most of the deaths due to NCD and injuries affected the productive young adult group and males. The burden caused by NCD in the most productive ages means that families, communities, and the nation at large suffer from premature deaths. The government of Tanzania must invest in early detection and timely treatment of NCDs to reduce premature deaths.

Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable routine surveillance data of malaria incidence, typically aggregated to administrative units, is becoming more widely available. Disaggregation regression is an important model framework for estimating high resolution risk maps from aggregated data. However, the aggregation of incidence over large, heterogeneous areas means that these data are underpowered for estimating complex, non-linear models. In contrast, prevalence point-surveys are directly linked to local environmental conditions but are not common in many areas of the world. Here, we train multiple non-linear, machine learning models on Plasmodium falciparum prevalence point-surveys. We then ensemble the predictions from these machine learning models with a disaggregation regression model that uses aggregated malaria incidences as response data. We find that using a disaggregation regression model to combine predictions from machine learning models improves model accuracy relative to a baseline model.

Background Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania. Methods This cross-sectional study involved reviews of documents, information systems and databases, and collection of primary data from facility-level registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Copies of monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system. Results A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate = 91.1%; interquartile range (IQR) 66.7–100%) and report forms (86.9%; IQR 62.2–100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR 35.6–100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%, and was low in urban districts. The availability rate at the district level was 65% (IQR 48–75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers’ records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly. Conclusion There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.

Background Histidine-rich protein 2 (HRP2)-based malaria rapid diagnostic tests (RDTs) are effective and widely used for the detection of wild-type Plasmodium falciparum infections. Although recent studies have reported false negative HRP2 RDT results due to pfhrp2 and pfhrp3 gene deletions in different countries, there is a paucity of data on the deletions of these genes in Tanzania. Methods A community-based cross-sectional survey was conducted between July and November 2017 in four regions: Geita, Kigoma, Mtwara and Ruvuma. All participants had microscopy and RDT performed in the field and provided a blood sample for laboratory multiplex antigen detection (for Plasmodium lactate dehydrogenase, aldolase, and P. falciparum HRP2). Samples showing RDT false negativity or aberrant relationship of HRP2 to pan-Plasmodium antigens were genotyped to detect the presence/absence of pfhrp2/3 genes. Results Of all samples screened by the multiplex antigen assay (n = 7543), 2417 (32.0%) were positive for any Plasmodium antigens while 5126 (68.0%) were negative for all antigens. The vast majority of the antigen positive samples contained HRP2 (2411, 99.8%), but 6 (0.2%) had only pLDH and/or aldolase without HRP2. Overall, 13 samples had an atypical relationship between a pan-Plasmodium antigen and HRP2, but were positive by PCR. An additional 16 samples with negative HRP2 RDT results but P. falciparum positive by microscopy were also chosen for pfhrp2/3 genotyping. The summation of false negative RDT results and laboratory antigen results provided 35 total samples with confirmed P. falciparum DNA for pfhrp2/3 genotyping. Of the 35 samples, 4 (11.4%) failed to consistently amplify positive control genes; pfmsp1 and pfmsp2 and were excluded from the analysis. The pfhrp2 and pfhrp3 genes were successfully amplified in the remaining 31 (88.6%) samples, confirming an absence of deletions in these genes. Conclusions This study provides evidence that P. falciparum parasites in the study area have no deletions of both pfhrp2 and pfhrp3 genes. Although single gene deletions could have been missed by the multiplex antigen assay, the findings support the continued use of HRP2-based RDTs in Tanzania for routine malaria diagnosis. There is a need for the surveillance to monitor the status of pfhrp2 and/or pfhrp3 deletions in the future.

Background Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control. Methods Using an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents. Findings We estimated 215·2 (95% uncertainty interval 143·7–311·6) million cases and 386·4 (307·8–497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7–326·8) million cases and 487·9 (385·3–634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7–342·5) million cases and 597·4 (468·0–784·4) thousand deaths with a 50% reduction; and 242·3 (158·7–358·8) million cases and 715·2 (556·4–947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%–75% also increased malaria burden to a total of 230·5 (151·6–343·3) million cases and 411·7 (322·8–545·5) thousand deaths with a 25% reduction; 232·8 (152·3–345·9) million cases and 415·5 (324·3–549·4) thousand deaths with a 50% reduction; and 234·0 (152·9–348·4) million cases and 417·6 (325·5–553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5–358·2) million cases and 520·9 (404·1–691·9) thousand deaths with a 25% reduction; 251·0 (162·2–377·0) million cases and 640·2 (492·0–856·7) thousand deaths with a 50% reduction; and 261·6 (167·7–396·8) million cases and 768·6 (586·1–1038·7) thousand deaths with a 75% reduction. Interpretation Under pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19. Funding Bill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

BackgroundIn 2015, a China-UK-Tanzania tripartite pilot project was implemented in southeastern Tanzania to explore a new model for reducing malaria burden and possibly scaling-out the approach into other malaria-endemic countries. The 1,7-malaria Reactive Community-based Testing and Response (1,7-mRCTR) which is a locally-tailored approach for reporting febrile malaria cases in endemic villages was developed to stop transmission andPlasmodiumlife-cycle. The (1,7-mRCTR) utilizes existing health facility data and locally trained community health workers to conduct community-level testing and treatment.MethodsThe pilot project was implemented from September 2015 to June 2018 in Rufiji District, southern Tanzania. The study took place in four wards, two with low incidence and two with a higher incidence. One ward of each type was selected for each of the control and intervention arms. The control wards implemented the existing Ministry of Health programmes. The 1,7-mRCTR activities implemented in the intervention arm included community testing and treatment of malaria infection. Malaria case-to-suspect ratios at health facilities (HF) were aggregated by villages, weekly to identify the village with the highest ratio. Community-based mobile test stations (cMTS) were used for conducting mass testing and treatment. Baseline (pre) and endline (post) household surveys were done in the control and intervention wards to assess the change in malaria prevalence measured by the interaction term of ‘time’ (post vs pre) and arm in a logistic model. A secondary analysis also studied the malaria incidence reported at the HFs during the intervention.ResultsOverall the 85 rounds of 1,7-mRCTR conducted in the intervention wards significantly reduced the odds of malaria infection by 66% (adjusted OR 0.34, 95% CI 0.26,0.44, p ConclusionThe 1,7-mRCTR approach significantly reduced the malaria burden in the areas of high transmission in rural southern Tanzania. This locally tailored approach could accelerate malaria control and elimination efforts. The results provide the impetus for further evaluation of the effectiveness and scaling up of this approach in other high malaria burden countries in Africa, including Tanzania.

BackgroundDespite high coverage and successes in malaria control strategies, some areas of Tanzania have indicated stagnantion or revesal of malaria burden. In malaria research, most studies are designed to assess drivers of malaria transmission focusing only on one dimension, single location while very few studies assess multiple components and their interactions at once. This article describes the protocol used to assess intrinsic and extrinsic drivers of persistent malaria transmission (hotsposts) in four regions from northwestern (Geita and Kigoma) and southern (Ruvuma and Mtwara) Tanzania.MethodsThis cross-sectional study was conducted between July and November 2017 in eight districts (two from each region). Based on the health facilities records, two villages were selected from each district. The study assessed five components individually and their linkages: socio-economic and malaria risk factors, parasitological, entomological, socio-anthropological and health system factors. Households (HHs) and household members were enumerated, socio-economic status and risk factors associated with malaria transmission were assessed. A total of 120 HHs were sampled from each village where malaria testing using rapid test and microscopy were done and blood spots on filter papers for genetic studies were collected. Heads of HHs were interviewed to capture information on knowledge, attitude, practice and beliefs towards malaria and its control. Assessment of adult mosquitoes in 25 HHs in each village and complimented with assessment of immature mosquitoes through larvae was conducted. The performance of the health system was assessed with respect to Information on availability, accessibility, affordability and quality of malaria prevention and case management services were collected from these health facilities.DiscussionThe proposed analysis plan and results from this study are expected to determine factors potentially responsible for persistence of malaria (hotspots) in the study areas. Rather than the traditional methodology of focusing on one metric, the approach proposed here triangulates observations from all five components, highlighting understanding of potential drivers while studying their complex interactions and map spatial heterogeneity. This study will provide an important framework and data which will guide future studies and malaria surveillance in Tanzania and other malaria endemic countries.

Background The world prevalence of community and hospital-acquired extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae is increasing tremendously. Bacteria harboring ESBLs are currently the number one critical pathogens posing a major threat to human health. Objective To provide a summary of molecular evidence on the prevalence of ESBL-producing Enterobacteriaceae (ESBL-E) and associated genes at community and hospital settings in East, Central, and Southern African countries. Methods We conducted a systematic literature search on PubMed and Google Scholar databases for the available molecular studies on ESBL-E in hospitals and community settings in East, Central, and Sothern Africa (ECSA). Published studies in English language involving gene characterization of ESBLs from human samples in hospital and community settings were included in the review, inception to November 2019. A random effect meta-analysis was performed to estimate the prevalence of ESBL-E. Results A total of 27 studies involving molecular characterization of resistance genes from 20,225 ESBL-E isolates were included in the analysis. Seventy-four percent of all studies were hospital based, 15% were based in community settings, and others were done in both hospital and community settings. Of all the studies, 63% reported E. coli as the dominant isolate among ESBL-E recovered from clinical samples and Klebsiella pneumoniae was reported dominant isolates in 33% of all studies. A random pooled prevalence of ESBL-E was 38% (95% CI = 24–53%), highest in Congo, 92% (95% CI = 90–94%), and lowest in Zimbabwe, 14% (95% CI = 9–20%). Prevalence was higher in hospital settings 41% (95% CI = 23–58%) compared to community settings 34% (95% CI = 8–60%). ESBL genes detected from clinical isolates with ESBL-E phenotypes in ECSA were those of Ambler molecular class A [1] that belongs to both functional groups 2be and 2d of Bush and Jacob classification of 2010 [2]. Majority of studies (n = 22, 81.5%) reported predominance of blaCTX-M gene among isolates, particularly CTX-M-15. Predictors of ESBL-E included increased age, hospital admissions, previous use of antibiotics, and paramedical use of herbs. Conclusion Few studies have been conducted at a molecular level to understand the genetic basis of increased resistance among members of ESBL-E in ECSA. Limited molecular studies in the ECSA region leave a gap in estimating the burden and risk posed by the carriage of ESBL genes in these countries. We found a high prevalence of ESBL-E most carrying CTX-M enzyme in ECSA with a greater variation between countries. This could be an important call for combined (regional or global) efforts to combat the problem of antimicrobial resistance (AMR) in the region. Antibiotic use and hospital admission increased the carriage of ESBL-E, while poor people contributed little to the increase of AMR due to lack of access and failure to meet the cost of healthcare compared to high income individuals.

High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programs, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania country-wide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, roughly separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from geographically close districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts, and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.SIGNIFICANCEDocumenting dynamics of malaria parasite genomics in high-transmission settings at scale in sub-Saharan Africa is critical for policy and decision making to support ongoing malaria elimination initiatives. Using molecular inversion probes, we genotyped over 1,000 Tanzanian Plasmodium falciparum samples collected country-wide in 2017 at hundreds of variable polymorphic positions across the genome. Frequencies of known drug resistance mutations were higher in northern districts of the country compared to the south. Results also showed a distinct isolation-by-distance pattern (whereby increasing geographic distance was correlated with decreasing genetic relatedness), as well as signals of higher genetic sharing between several southern districts. These results provide, for the first time, a picture of current within-country diversity of Tanzanian P. falciparum populations.

Background Agro-ecological systems have been associated with increased malaria intensity. This study determined association between different agro-ecological systems, prevalence of malaria parasitaemia and anaemia in Mvomero district, Tanzania. Methods The study was carried out in three agro-ecosystems namely, savannah, rice-irrigation, and sugarcane. Malaria and anaemia prevalence were measured in four seasons of a year. Villages were categorized according to environmental characteristics, proportion of water-shaded areas and agro-ecosystems. Mixed-effects logistic regression analysis was used to determine factors associated with malaria infection. Results A total of 7888 individuals were involved with the overall malaria prevalence of 34.4%. Plasmodium falciparum was the dominant (99.52%) malaria species. Malaria prevalence was highest (42.9%) in children of 10–15 years of age, and significantly low during dry and hot season. Of the infected individuals, 78.1% were from rice-irrigation, 18.7% savannah and 3.2% sugarcane ecosystem. Individuals living in villages with high levels of water-shaded areas had highest malaria risk. Over three-quarters (78.9%) of the individuals slept under a mosquito net, with the highest (88.5%) coverage among individuals in sugarcane ecosystem. On average 47.1% of the children were anaemic. Anaemia was more prevalent (60.5%) among individuals in the savannah than in the rice-irrigation (48.2%) or sugarcane communities (23%). Analysis indicated that ecosystems and levels of water-shaded area were highly correlated, and altered levels of malaria infection. Gender, age, mosquito net-use, and season were other significant determinants of P. falciparum infection. Males had higher odds than females (OR = 1.16, 95% CI 1.05, 1.29). The risk for children 6–9 years and older children (10–15 years) was over 50% and 24%, respectively, higher compared to young ones (0–5 years). Use of mosquito net reduced malaria risk by 26%. The risk of infection was higher during dry and cool season (OR = 1.92, 95 %CI 1.66, 2.23) compared to other seasons. Living in villages with high level of water-shaded areas increased the chances of getting malaria up to 15 times than living in drier areas. Similarly, infection odds increased when living in savannah and rice-irrigation ecosystems than in the sugarcane ecosystem. Conclusions Findings show significant variations in malaria prevalence between communities living in different agro-ecosystems within the same district. Local malaria control strategies should consider these variations and liaise with agricultural experts while designing interventions to maximize effectiveness.

Access to healthcare is a requirement for human well-being that is constrained, in part, by the allocation of healthcare resources relative to the geographically dispersed human population(1-3). Quantifying access to care globally is challenging due to the absence of a comprehensive database of healthcare facilities. We harness major data collection efforts underway by OpenStreetMap, Google Maps and academic researchers to compile the most complete collection of facility locations to date. Leveraging the geographically variable strengths of our facility datasets, we use an established methodology(4)to characterize travel time to healthcare facilities in unprecedented detail. We produce maps of travel time with and without access to motorized transport, thus characterizing travel time to healthcare for populations distributed across the wealth spectrum. We find that just 8.9% of the global population (646 million people) cannot reach healthcare within one hour if they have access to motorized transport, and that 43.3% (3.16 billion people) cannot reach a healthcare facility by foot within one hour. Our maps highlight an additional vulnerability faced by poorer individuals in remote areas and can help to estimate whether individuals will seek healthcare when it is needed, as well as providing an evidence base for efficiently distributing limited healthcare and transportation resources to underserved populations both now and in the future. A global analysis generating high-resolution maps of travel time shows that 91.1% of the world's population can reach a hospital or clinic within an hour if they have access to motorized transportation, but only 56.7% can do so by walking, highlighting additional inequities for underserved populations accessing healthcare.

PURPOSE This retrospective study sought to determine the type, burden, and pattern of cancer deaths in public hospitals in Tanzania from 2006 to 2015. METHODS This study analyzed data on cancer mortality in 39 hospitals in Tanzania. Data on the age and sex of the deceased and type of cancer were extracted from hospital death registers and report forms. Cancer types were grouped according to the 10th revision of the International Classification of Diseases. Age-standardized mortality rates and cancer mortality patterns were analyzed. A χ2 test was used to examine the association between common cancers and selected covariates. RESULTS A total of 12,621 cancer-related deaths occurred during the 10-year period, which translates to an age-standardized hospital-based mortality rate of 47.8 per 100,000 population. Overall, the number of deaths was notably higher (56.5%) among individuals in the 15- to 59-year-old age category and disproportionately higher among females than males ( P = .0017). Cancers of the cervix, esophagus, and liver were the 3 major causes of death across all study hospitals in Tanzania. Cancers of the cervix, esophagus, and liver were the largest contributors to mortality burden among females. Among males, cancers of the esophagus, liver, and prostate were the leading cause of mortality. CONCLUSION There is an increasing trend in cancer mortality over recent years in Tanzania, which differs with respect to age, sex, and geographic zones. These findings provide a basis for additional studies to ascertain incidence rates and survival probabilities, and highlight the need to strengthen awareness campaigns for early detection, access to care, and improved diagnostic capabilities.

SummaryAs malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low prevalence areas are increasingly needed. For low burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in areas with both routine surveillance data and prevalence surveys, models that make use of the spatial information from prevalence point-surveys have great potential. Using case studies in Indonesia, Senegal and Madagascar, we compare two methods for incorporating point-level, spatial information into disaggregation regression models. The first simply fits a Gaussian random field to prevalence point-surveys to create a new covariate. The second is a multi-likelihood model that is fitted jointly to prevalence point-surveys and polygon incidence data. We find that the simple model generally performs better than a baseline disaggregation model while the joint model performance was mixed. More generally, our results demonstrate that combining these types of data improves estimates of malaria incidence.

Background Salmonellosis remains an important public health problem globally. The disease is among the leading causes of morbidity and mortality in developing countries that experience poor hygiene and lack of access to clean and safe water. There was an increase in reported cases of Salmonellosis in Njombe Region, Southern Highland of Tanzania between 2015 and 2016 based on clinical diagnosis. Nevertheless, little is known about the factors contributing to the transmission of this disease in the region. This study was conducted to determine the prevalence, antimicrobial susceptibility, and factors associated with Salmonella infection among patients who report gastrointestinal complaints. Methods A cross-sectional study was conducted from December 2017 to February 2018 among patients with gastrointestinal complaints at Kibena Regional Hospital. Stool samples were submitted for isolation of Salmonella spp. Identification was based on conventional biochemical tests and serotyping to differentiate typhoid and non-typhoid Salmonella (NTS). Antimicrobial susceptibility was performed using the Kirby-Bauer disc diffusion method. Multivariable logistic regression analysis was performed to examine the factors independently associated with Salmonella infection. Results The prevalence of Salmonella infection among participants with gastrointestinal complaints was 16.5% (95% CI: 12.7–21.1) of them, 83.7, 95% CI: 70.9–91.5 were NTS while 16.3, 95% CI: 8.5–29.0 were Typhoid Salmonella species. All isolates were sensitive to ceftriaxone and ciprofloxacin, whereas 27.8 and 100% were resistant to co-trimoxazole and ampicillin respectively. The odd of Salmonella infection was fourfold higher among participants with formal employment (AOR 3.8, 95% CI, 1.53–9.40). Use of water from wells/rivers (AOR 2.2, 95% CI, 1.07–4.45), drinking untreated water (AOR 2.6, 95% CI, 1.21–5.48) and often eating at a restaurant (AOR 3.4, 95% CI, 1.28–8.93) had increased odds of Salmonella infection. Likewise, having abdominal pain (AOR 8.5, 95% CI, 1.81–39.78) and diarrhea (AOR 2.3, 95% CI, 1.12–4.68) were independent symptoms that predict Salmonella infection. Conclusion There is a high prevalence of Salmonella infection among people who report gastrointestinal complaints and it is clinically predicated by diarhoea and abdominal pain. Employed participants and those eating at restaurant and drinking unsafe water had higher risk of infection. Salmonella spp. causing gastroenteritis has developed resistance to commonly used antibiotics.

Background: Toxoplasmosis caused by the obligate intracellular coccidian protozoan Toxoplasma gondii (T. gondii) infects all warm-blooded animals including humans. This parasite may develop in both immune-compromised and immunocompetent hosts but usually the disease manifestations strongly differ according to immune status. Immunocompromised hosts develop more severe disease than immunocompetent hosts. Infections in pregnancy carry the risk of foetal involvement and can lead to serious clinical outcomes including psychomotor and ocular disorders in congenitally infected foetuses and children.Objective: To assess the level of awareness and practices towards congenital toxoplasmosis among health workers and pregnant women in Tanzania’s Temeke municipality.Methods: This was a cross-sectional study involving 371 pregnant women and 22 health workers from six healthcare facilities in Temeke municipality of Dar es Salaam, Tanzania. A structured questionnaire and review of prenatal screening forms were used to collect information. The questionnaire focused on knowledge of disease aetiology, signs and symptoms, modes of transmission, treatment and management.Results: Of the pregnant women, 96% (95% CI: 0. 94-0.98) were unaware of the disease, had never heard, read or seen any information regarding toxoplasmosis. The majority of respondents including those who had heard, read or seen information concerning toxoplasmosis were unaware of the disease aetiology, signs and symptoms. However, 90% (95% CI: 0.86–0.93) of respondents unknowingly observed preventive practices towards the disease including avoiding eating raw, cured or rare meat. There was a significant statistical relationship between practices towards toxoplasmosis and age of pregnant women, such that for every increase in age by ten years the risk practices towards toxoplasmosis increased by 41% (OR=1.41, 95%, C.I. 1.05-1.90). Preventive practices towards toxoplasmosis decreased significantly by 74% and 78% for the age of 19-25 and 26-35 years old pregnant women respectively, as compared to those < 19 years. No significant difference was observed for those aged > 35 years. Multigravidae was associated with at-risk practices towards toxoplasmosis (OR=2.65, CI: 1.38-5.08). Of the 22 health workers who participated in the study, 36% (95% CI: 0.15–0.58) were aware of the congenital toxoplasmosis and its clinical outcomes. None of them had diagnosed the disease before.Conclusion: Due to general lack of awareness towards toxoplasmosis observed among both health workers and pregnant women in Temeke Municipality, we recommend health policy on maternal and child healthcare to address prenatal screening that is aimed at providing early diagnosis for any possible congenital toxoplasmosis as well as diseases that are currently screened in Tanzania such as HIV, syphilis and malaria. Integrating a One Health approach in educating medical professionals and the vulnerable population of pregnant women on the importance of congenital zoonoses will promote awareness and preventive practices towards the disease.Keywords: Toxoplasmosis awareness, pregnant women, health workers, Dar es Salaam, Tanzania.

Publisher's version (útgefin grein), Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990-2010 time period, with the greatest annualised rate of decline occurring in the 0-9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10-24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10-24 years were also in the top ten in the 25-49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50-74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd., Research reported in this publication was supported by the Bill & Melinda Gates Foundation; the University of Melbourne; Queensland Department of Health, Australia; the National Health and Medical Research Council, Australia; Public Health England; the Norwegian Institute of Public Health; St Jude Children's Research Hospital; the Cardiovascular Medical Research and Education Fund; the National Institute on Ageing of the National Institutes of Health (award P30AG047845); and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The authors alone are responsible for the views expressed in this Article and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated, the National Health Service (NHS), the National Institute for Health Research (NIHR), the UK Department of Health and Social Care, or Public Health England; the United States Agency for International Development (USAID), the US Government, or MEASURE Evaluation; or the European Centre for Disease Prevention and Control (ECDC). This research used data from the Chile National Health Survey 2003, 2009-10, and 2016-17. The authors are grateful to the Ministry of Health, the survey copyright owner, for allowing them to have the database. All results of the study are those of the authors and in no way committed to the Ministry. The Costa Rican Longevity and Healthy Aging Study project is a longitudinal study by the University of Costa Rica's Centro Centroamericano de Poblacion and Instituto de Investigaciones en Salud, in collaboration with the University of California at Berkeley. The original pre-1945 cohort was funded by the Wellcome Trust (grant 072406), and the 1945-55 Retirement Cohort was funded by the US National Institute on Aging (grant R01AG031716). The principal investigators are Luis Rosero-Bixby and William H Dow and co-principal investigators are Xinia Fernandez and Gilbert Brenes. The accuracy of the authors' statistical analysis and the findings they report are not the responsibility of ECDC. ECDC is not responsible for conclusions or opinions drawn from the data provided. ECDC is not responsible for the correctness of the data and for data management, data merging and data collation after provision of the data. ECDC shall not be held liable for improper or incorrect use of the data. The Health Behaviour in School-Aged Children (HBSC) study is an international study carried out in collaboration with WHO/EURO. The international coordinator of the 1997-98, 2001-02, 2005-06, and 2009-10 surveys was Candace Currie and the databank manager for the 1997-98 survey was Bente Wold, whereas for the following surveys Oddrun Samdal was the databank manager. A list of principal investigators in each country can be found on the HBSC website. Data used in this paper come from the 2009-10 Ghana Socioeconomic Panel Study Survey, which is a nationally representative survey of more than 5000 households in Ghana. The survey is a joint effort undertaken by the Institute of Statistical, Social and Economic Research (ISSER) at the University of Ghana and the Economic Growth Centre (EGC) at Yale University. It was funded by EGC. ISSER and the EGC are not responsible for the estimations reported by the analysts. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with license number SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law, 2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. Data for this research was provided by MEASURE Evaluation, funded by USAID. The authors thank the Russia Longitudinal Monitoring Survey, conducted by the National Research University Higher School of Economics and ZAO Demoscope together with Carolina Population Center, University of North Carolina at Chapel Hill and the Institute of Sociology, Russia Academy of Sciences for making data available. This paper uses data from the Bhutan 2014 STEPS survey, implemented by the Ministry of Health with the support of WHO; the Kuwait 2006 and 2014 STEPS surveys, implemented by the Ministry of Health with the support of WHO; the Libya 2009 STEPS survey, implemented by the Secretariat of Health and Environment with the support of WHO; the Malawi 2009 STEPS survey, implemented by Ministry of Health with the support of WHO; and the Moldova 2013 STEPS survey, implemented by the Ministry of Health, the National Bureau of Statistics, and the National Center of Public Health with the support of WHO. This paper uses data from Survey of Health, Ageing and Retirement in Europe (SHARE) Waves 1 (DOI:10.6103/SHARE. w1.700), 2 (10.6103/SHARE.w2.700), 3 (10.6103/SHARE.w3.700), 4 (10.6103/SHARE.w4.700), 5 (10.6103/SHARE.w5.700), 6 (10.6103/SHARE.w6.700), and 7 (10.6103/SHARE.w7.700); see Borsch-Supan and colleagues (2013) for methodological details. The SHARE data collection has been funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N degrees 211909, SHARE-LEAP: GA N degrees 227822, SHARE M4: GA N degrees 261982) and Horizon 2020 (SHARE-DEV3: GA N degrees 676536, SERISS: GA N degrees 654221) and by DG Employment, Social Affairs & Inclusion. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C), and from various national funding sources is gratefully acknowledged. This study has been realised using the data collected by the Swiss Household Panel, which is based at the Swiss Centre of Expertise in the Social Sciences. The project is financed by the Swiss National Science Foundation. The United States Aging, Demographics, and Memory Study is a supplement to the Health and Retirement Study (HRS), which is sponsored by the National Institute of Aging (grant number NIA U01AG009740). It was conducted jointly by Duke University and the University of Michigan. The HRS is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan. This paper uses data from Add Health, a program project designed by J Richard Udry, Peter S Bearman, and Kathleen Mullan Harris, and funded by a grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due to Ronald R Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website. No direct support was received from grant P01-HD31921 for this analysis. The data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US Government. Collection of data for the Mozambique National Survey on the Causes of Death 2007-08 was made possible by USAID under the terms of cooperative agreement GPO-A-00-08-000_D3-00. This manuscript is based on data collected and shared by the International Vaccine Institute (IVI) from an original study IVI conducted. L G Abreu acknowledges support from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (Brazil; finance code 001) and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, a Brazilian funding agency). I N Ackerman was supported by a Victorian Health and Medical Research Fellowship awarded by the Victorian Government. O O Adetokunboh acknowledges the South African Department of Science and Innovation and the National Research Foundation. A Agrawal acknowledges the Wellcome Trust DBT India Alliance Senior Fellowship. S M Aljunid acknowledges the Department of Health Policy and Management, Faculty of Public Health, Kuwait University and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia for the approval and support to participate in this research project. M Ausloos, C Herteliu, and A Pana acknowledge partial support by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. A Badawi is supported by the Public Health Agency of Canada. D A Bennett was supported by the NIHR Oxford Biomedical Research Centre. R Bourne acknowledges the Brien Holden Vision Institute, University of Heidelberg, Sightsavers, Fred Hollows Foundation, and Thea Foundation. G B Britton and I Moreno Velasquez were supported by the Sistema Nacional de Investigacion, SNI-SENACYT, Panama. R Buchbinder was supported by an Australian National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship. J J Carrero was supported by the Swedish Research Council (2019-01059). F Carvalho acknowledges UID/MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/MCTES through national funds. A R Chang was supported by National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases grant K23 DK106515. V M Costa acknowledges the grant SFRH/BHD/110001/2015, received by Portuguese national funds through Fundacao para a Ciencia e Tecnologia, IP, under the Norma Transitaria DL57/2016/CP1334/CT0006. A Douiri acknowledges support and funding from the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care South London at King's College Hospital NHS Foundation Trust and the Royal College of Physicians, and support from the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. B B Duncan acknowledges grants from the Foundation for the Support of Research of the State of Rio Grande do Sul (IATS and PrInt) and the Brazilian Ministry of Health. H E Erskine is the recipient of an Australian NHMRC Early Career Fellowship grant (APP1137969). A J Ferrari was supported by a NHMRC Early Career Fellowship grant (APP1121516). H E Erskine and A J Ferrari are employed by and A M Mantilla-Herrera and D F Santomauro affiliated with the Queensland Centre for Mental Health Research, which receives core funding from the Queensland Department of Health. M L Ferreira holds an NHMRC Research Fellowship. C Flohr was supported by the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust. M Freitas acknowledges financial support from the EU (European Regional Development Fund [FEDER] funds through COMPETE POCI-01-0145-FEDER-029248) and National Funds (Fundacao para a Ciencia e Tecnologia) through project PTDC/NAN-MAT/29248/2017. A L S Guimaraes acknowledges support from CNPq. C Herteliu was partially supported by a grant co-funded by FEDER through Operational Competitiveness Program (project ID P_40_382). P Hoogar acknowledges Centre for Bio Cultural Studies, Directorate of Research, Manipal Academy of Higher Education and Centre for Holistic Development and Research, Kalaghatagi. F N Hugo acknowledges the Visiting Professorship, PRINT Program, CAPES Foundation, Brazil. B-F Hwang was supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. S M S Islam was funded by a National Heart Foundation Senior Research Fellowship and supported by Deakin University. R Q Ivers was supported by a research fellowship from the National Health and Medical Research Council of Australia. M Jakovljevic acknowledges the Serbian part of this GBD-related contribution was co-funded through Grant OI175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. P Jeemon was supported by a Clinical and Public Health intermediate fellowship (grant number IA/CPHI/14/1/501497) from the Wellcome Trust-Department of Biotechnology, India Alliance (2015-20). O John is a recipient of UIPA scholarship from University of New South Wales, Sydney. S V Katikireddi acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_12017/13, MC_UU_12017/15), and the Scottish Government Chief Scientist Office (SPHSU13, SPHSU15). C Kieling is a CNPq researcher and a UK Academy of Medical Sciences Newton Advanced Fellow. Y J Kim was supported by Research Management Office, Xiamen University Malaysia (XMUMRF/2018-C2/ITCM/00010). K Krishan is supported by UGC Centre of Advanced Study awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar was supported by K43 TW 010716 FIC/NIMH. B Lacey acknowledges support from the NIHR Oxford Biomedical Research Centre and the BHF Centre of Research Excellence, Oxford. J V Lazarus was supported by a Spanish Ministry of Science, Innovation and Universities Miguel Servet grant (Instituto de Salud Carlos III [ISCIII]/ESF, the EU [CP18/00074]). K J Looker thanks the NIHR Health Protection Research Unit in Evaluation of Interventions at the University of Bristol, in partnership with Public Health England, for research support. S Lorkowski was funded by the German Federal Ministry of Education and Research (nutriCARD, grant agreement number 01EA1808A). R A Lyons is supported by Health Data Research UK (HDR-9006), which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, NIHR (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome Trust. J J McGrath is supported by the Danish National Research Foundation (Niels Bohr Professorship), and the Queensland Health Department (via West Moreton HHS). P T N Memiah acknowledges support from CODESRIA. U O Mueller gratefully acknowledges funding by the German National Cohort Study BMBF grant number 01ER1801D. S Nomura acknowledges the Ministry of Education, Culture, Sports, Science, and Technology of Japan (18K10082). A Ortiz was supported by ISCIII PI19/00815, DTS18/00032, ISCIII-RETIC REDinREN RD016/0009 Fondos FEDER, FRIAT, Comunidad de Madrid B2017/BMD-3686 CIFRA2-CM. These funding sources had no role in the writing of the manuscript or the decision to submit it for publication. S B Patten was supported by the Cuthbertson & Fischer Chair in Pediatric Mental Health at the University of Calgary. G C Patton was supported by an aNHMRC Senior Principal Research Fellowship. M R Phillips was supported in part by the National Natural Science Foundation of China (NSFC, number 81371502 and 81761128031). A Raggi, D Sattin, and S Schiavolin were supported by grants from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C Besta, Linea 4-Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). P Rathi and B Unnikrishnan acknowledge Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal. A L P Ribeiro was supported by Brazilian National Research Council, CNPq, and the Minas Gerais State Research Agency, FAPEMIG. D C Ribeiro was supported by The Sir Charles Hercus Health Research Fellowship (#18/111) Health Research Council of New Zealand. D Ribeiro acknowledges financial support from the EU (FEDER funds through the Operational Competitiveness Program; POCI-01-0145-FEDER-029253). P S Sachdev acknowledges funding from the NHMRC of Australia Program Grant. A M Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. M M Santric-Milicevic acknowledges the Ministry of Education, Science and Technological Development of the Republic of Serbia (contract number 175087). R Sarmiento-Suarez received institutional support from Applied and Environmental Sciences University (Bogota, Colombia) and ISCIII (Madrid, Spain). A E Schutte received support from the South African National Research Foundation SARChI Initiative (GUN 86895) and Medical Research Council. S T S Skou is currently funded by a grant from Region Zealand (Exercise First) and a grant from the European Research Council under the EU's Horizon 2020 research and innovation program (grant agreement number 801790). J B Soriano is funded by Centro de Investigacion en Red de Enfermedades Respiratorias, ISCIII. R Tabares-Seisdedos was supported in part by the national grant PI17/00719 from ISCIII-FEDER. N Taveira was partially supported by the European & Developing Countries Clinical Trials Partnership, the EU (LIFE project, reference RIA2016MC-1615). S Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral programme (reference number CD15/00019 from ISCIII-FEDER). S B Zaman received a scholarship from the Australian Government research training programme in support of his academic career., "Peer Reviewed"

BackgroundMortality statistics are traditionally used to quantify the burden of disease and to determine the relative importance of the various causes of death. Some of the most frequently used indices to quantify the burden of disease are the years of potential life lost (YPLL) and years of potential productive life lost (YPPLL). These two measures reflect the mortality trends in younger age groups and they provide a more accurate picture of premature mortality. This study was carried out to determine YPLL, YPPLL and cost of productivity lost (CPL) due to premature mortality caused by selected causes of deaths in Tanzania.Methods and findingsMalaria, respiratory diseases, HIV/AIDS, tuberculosis, cancers and injuries were selected for this analysis. The number of deaths by sex and age groups were obtained from hospital death registers and ICD-10 reporting forms in 39 public hospitals in Tanzania, covering a period of 2006-2015. The life expectancy method and human capital approach were used to estimate the YPLL, YPPLL and CPL due to premature mortality. During 2006-2015, malaria, HIV/AIDS, tuberculosis, respiratory diseases, HIV+tuberculosis, cancer and injury were responsible for a total of 96,834 hospital deaths, of which 46.4% (n = 57,508) were among individuals in the productive age groups (15-64 years). The reported deaths contributed to 2,850,928 YPLL (female = 1,326,724; male = 1,524,205) with an average of 29 years per death. The average YPLL among females (32) was higher than among males (28). Malaria (YPLL = 38 per death) accounted for over one-third (35%) of the total YPLL. There was a significant increase in YPLL due to the selected underlying causes of death over the 10-year period. Deaths from the selected causes resulted into 1,207,499 YPPLL (average = 21 per death). Overall, HIV/AIDS contributed to the highest YPPLL (323,704), followed by malaria (243,490) and injuries (196,505). While there was a general decrease in YPPLL due to malaria, there was an increase of YPPLL due to HIV/AIDS, respiratory diseases, cancer and injuries during the 10-year period. The total CPL due to the six diseases was US$ 148,430,009 for 10 years. The overall CPL was higher among males than females by 29.1%. Over half (58%) of the losses were due to deaths among males. HIV/AIDS accounted for the largest (29.2%) CPL followed by malaria (17.8%) and respiratory diseases (14.6%). The CPL increased from US$11.4 million in 2006 to US$17.9 million in 2016.ConclusionsThe YPLL, YPPLL and CPL due to premature death associated with the six diseases in Tanzania are substantially high. While malaria accounted for highest YPLL, HIV/AIDS accounted for highest YPPLL and CPL. The overall CPL was higher among males than among females. Setting resource allocation priorities to malaria, HIV/AIDS and respiratory diseases that are responsible for the majority of premature deaths could potentially reduce the costs of productivity loss in Tanzania.

Malaria transmission in Madagascar is highly heterogeneous, exhibiting spatial, seasonal and long-term trends. Previous efforts to map malaria risk in Madagascar used prevalence data from Malaria Indicator Surveys. These cross-sectional surveys, conducted during the high transmission season most recently in 2013 and 2016, provide nationally representative prevalence data but cover relatively short time frames. Conversely, monthly case data are collected at health facilities but suffer from biases, including incomplete reporting and low rates of treatment seeking. We combined survey and case data to make monthly maps of prevalence between 2013 and 2016. Health facility catchment populations were estimated to produce incidence rates from the case data. Smoothed incidence surfaces, environmental and socioeconomic covariates, and survey data informed a Bayesian prevalence model, in which a flexible incidence-to-prevalence relationship was learned. Modelled spatial trends were consistent over time, with highest prevalence in the coastal regions and low prevalence in the highlands and desert south. Prevalence was lowest in 2014 and peaked in 2015 and seasonality was widely observed, including in some lower transmission regions. These trends highlight the utility of monthly prevalence estimates over the four year period. By combining survey and case data using this two-step modelling approach, we were able to take advantage of the relative strengths of each metric while accounting for potential bias in the case data. Similar modelling approaches combining large datasets of different malaria metrics may be applicable across sub-Saharan Africa.

Background: In 2015, a China-UK-Tanzania tripartite pilot project was implemented in south-eastern Tanzania to explore a new model to reduce the malaria burden with the aim of eventually scaling-up the approach in Africa. Chinese and Tanzanian teams have developed a locally-tailored malaria control approach screening for febrile cases in endemic villages on Day 1 followed by focal treatment of holoendemic villages within 7 days to stop transmission at the same phase of the plasmodium life-cycle. This 1,7-Reactive Community-based Testing and Response (1,7-mRCT) model can utilize existing health facility data and locally trained community-based health workers to conduct community-level testing and treatment. Methods: Matched malaria incidence pairs of control and intervention wards were chosen. The latter arm was selected for the 1,7-mRCT approach, while the control wards relied on long-lasting insecticide-treated bednets only. The 1,7-mRCT activities included community testing and treatment of malaria infection. Case-to-suspect ratios of malaria cases were aggregated at the village level weekly to identify the village with the highest ratio. Community-based mobile test stations (cMTS) were used for mass testing and treatment. The pilot project was implemented from September 2015 to June 2018 with 85 rounds of 1,7-mRCT implemented in the intervention wards. Comparing the two arms of approach we look for any change in malaria prevalence from the baseline to the endline survey. Besides we also studied the malaria incidence reported at the health facilities after interventions in the treated villages. Findings: Compared to the control wards, the 1,7-mRCT model significantly reduced the malaria infections by 66% (adjusted OR 0.34, 95%CI 0.26-0.44, p

Background Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we construct a statistical modelling framework for characterising the seasonal patterns derived directly from monthly health facility data. Methods With data from 2669 of the 3247 health facilities in Madagascar, a spatiotemporal regression model was used to estimate seasonal patterns across the island. In the absence of catchment population estimates or the ability to aggregate to the district level, this focused on the monthly proportions of total annual cases by health facility level. The model was informed by dynamic environmental covariates known to directly influence seasonal malaria trends. To identify operationally relevant characteristics such as the transmission start months and associated uncertainty measures, an algorithm was developed and applied to model realisations. A seasonality index was used to incorporate burden information from household prevalence surveys and summarise ‘how seasonal’ locations are relative to their surroundings. Results Positive associations were detected between monthly case proportions and temporally lagged covariates of rainfall and temperature suitability. Consistent with the existing literature, model estimates indicate that while most parts of Madagascar experience peaks in malaria transmission near March–April, the eastern coast experiences an earlier peak around February. Transmission was estimated to start in southeast districts before southwest districts, suggesting that indoor residual spraying should be completed in the same order. In regions where the data suggested conflicting seasonal signals or two transmission seasons, estimates of seasonal features had larger deviations and therefore less certainty. Conclusions Monthly health facility data can be used to establish seasonal patterns in malaria burden and augment the information provided by household prevalence surveys. The proposed modelling framework allows for evidence-based and cohesive inferences on location-specific seasonal characteristics. As health surveillance systems continue to improve, it is hoped that more of such data will be available to improve our understanding and planning of intervention strategies.

OBJECTIVE To determine the causes, patterns and trends of respiratory diseases-related deaths in hospitals of Tanzania 2006-2015. METHODS Retrospective study involving 39 hospitals. Medical records of patients who died in hospital were retrieved, reviewed and analysed. Sources of data were hospital admission registers, death registers and International Classification of Diseases report forms. Information on demographic characteristics, date of death, the immediate underlying cause of death and co-morbid conditions was collected. RESULTS Of the 247 976 deaths reported during the 10-year period, respiratory diseases accounted for 12.92% (n = 32 042). The majority of the respiratory mortality was reported among males (55.9%). Overall median age at death was 31 years with an interquartile range (IQR) of 1-47. Median age at death was significantly higher among males (35 years) than females (28 years) (P

Background Accurate and reliable hospital information on the pattern and causes of death is important to monitor and evaluate the effectiveness of health policies and programs. The objective of this study was to assess the availability, accessibility, and quality of hospital mortality data in Tanzania. Methods This cross-sectional study involved selected hospitals of Tanzania and was carried out from July to October 2016. Review of hospital death registers and forms was carried out to cover a period of 10 years (2006–2015). Interviews with hospital staff were conducted to seek information as regards to tools used to record mortality data, staff involved in recording and availability of data storage and archiving facilities. Results A total of 247,976 death records were reviewed. The death register was the most (92.3%) common source of mortality data. Other sources included the International Classification of Diseases (ICD) report forms, Inpatient registers, and hospital administrative reports. Death registers were available throughout the 10-year period while ICD-10 forms were available for the period of 2013–2015. In the years between 2006 and 2010 and 2011–2015, the use of death register increased from 82 to 94.9%. Three years after the introduction of ICD-10 procedure, the forms were available and used in 28% (11/39) hospitals. The level of acceptable data increased from 69% in 2006 to 97% in 2015. Inconsistency in the language used, use of non-standard nomenclature for causes of death, use of abbreviations, poorly and unreadable handwriting, and missing variables were common data quality challenges. About 6.3% (n = 15,719) of the records had no patient age, 3.5% (n = 8790) had no cause of death and ~ 1% had no sex indicated. The frequency of missing sex variable was most common among under-5 children. Data storage and archiving in most hospitals was generally poor. Registers and forms were stored in several different locations, making accessibility difficult. Conclusion Overall, this study demonstrates gaps in hospital mortality data availability, accessibility, and quality, and highlights the need for capacity strengthening in data management and periodic record reviews. Policy guidelines on the data management including archiving are necessary to improve data.

Background Malaria remains the most important cause of morbidity and mortality in Tanzania. However, its prevalence varies from area to area depending on various ecological, socio-economic and health system factors. This study was carried out to determine malaria prevalence and associated factors among rice farming communities in the Kilangali village of Kilosa District in Central Tanzania. Methods A cross-sectional study was conducted in May 2015, involving randomly selected persons living in the six sub-villages of the Kilangali village, namely Mlegeni, Kisiwani, Makuruwili, Kwamtunga, Upogoroni and Chamwino. A finger prick blood sample was obtained for diagnosis of malaria infection using Giemsa-stained thick smears and a rapid malaria diagnostic test. Study participants were also screened for haemoglobin levels and a total of 570 children aged ≤ 12 years of age were examined for spleen enlargement using the palpation method. Results A total of 1154 persons were examined for malaria infection with mean age of 21.9 ± 19.69 years. The overall malaria prevalence was 14.2% and 17.5% based on microscopic examination and rapid diagnostic test, respectively. Plasmodium falciparum accounted for the majority (89%) of the malaria infections. The overall geometrical mean parasite density was 20.5 parasites/μL (95% CI: 14.6–28.8). Malaria prevalence and parasitaemia was highest among individuals living in the Mlegeni (23.9%) and Makuruwili (24.4%) sub-villages. Among the children examined for splenomegaly, 2.98% (17/570) had it. The overall prevalence of anaemia was 34.6%. Malaria infection was associated with the age groups of 1–10 years (aOR = 4.41, 95% CI: 1.96–9.93, P

Background Uptake of Human Immunodeficiency Virus (HIV) re-testing among postnatal mothers who had previously tested HIV-negative is crucial for the detection of recent seroconverters who are likely to have high plasma viral loads and an increased risk of mother-to-child HIV transmission. Tanzania set a target of 90% re-testing of pregnant mothers who had tested negative during the first test. However, there is no statistics on the implementation, coverage and the factors determining re-testing among pregnant women in Tanzania. This study determined the proportion of newly-delivered, previously HIV-negative mothers who returned for HIV re-testing, and assessed the determinants of re-testing in Njombe Region in Tanzania. Methods A cross-sectional study was conducted in four health facilities in Njombe and Wanging’ombe districts during December 2015–June 2016. All newly-delivered mothers (≤7 days from delivery) presenting at health facilities and who had previously tested HIV-negative during pregnancy were included. A structured questionnaire was used to collect data on the determinants for re-testing. Records on the previous HIV testing was verified using antenatal clinic card. A multiple logistic regression model was used to calculate the adjusted odds ratio (AOR) with their 95% confidence intervals (CI) to quantify the association. Results Of 668 mothers (median age = 25 years) enrolled, 203 (30.4%) were re-tested for their HIV status. Among these, 27 (13.3%) tested positive. Significant predictors for HIV re-testing were socio-demographic factors including having at least a secondary education [AOR = 1.9, 95% CI: 1.25–3.02] and being employed [AOR = 2.1, 95% CI: 1.06–4.34]; personal and behavioural factors, reporting symptoms of sexually transmitted infections [AOR = 4.9, 95% CI: 2.15–6.14] and use of condoms during intercourse [AOR = 1.7, 95% CI: 1.13–2.71]. Significant health system factors were having ≥4 ANC visits [AOR = 1.8, 95% CI: 1.21–2.69] and perceiving good quality of HIV counselling and testing service at the first ANC visit [AOR = 2.14, 95% CI: 1.53–3.04]. Conclusion Uptake of the HIV re-testing was lower than the national target. Education level, employment status, having ≥4 ANC visits, reporting sexually-transmitted infections, condom use, and good perception of HIV tests were significant factors increased uptake for re-testing. Identified factors should be incorporated in the Prevention of the Mother-to-Child Transmission (PMTCT) programme strategies to prevent HIV infection in new-borns.

Background The use of larval source management as a supplementary intervention for malaria control has not been widely used in rural Africa due to perceived high costs and complex logistics. To reduce the cost of larviciding in rice farming communities, concurrent application of biolarvicides and fertilizer in rice fields was introduced to control malaria vectors larvae and improve rice grain yields. The present study determined rice farmers’ perceptions and acceptability in the use of a combination of biolarvicide and fertilizers in farming practices. Methods This was a qualitative study conducted among rice farmers at Kilangali village, south-central Tanzania. Semi-structured interviews and three focus group discussions (FGDs) were conducted with men and women who participated in the biolarvicide and fertilizer application project. The interviews and discussion focused on knowledge, attitudes and perceptions of participants on the use of the innovation in their farming practices and their willingness to pay for the innovation. Results A total of 40 (mean age = 38.8 ± 10.12 years) rice farmers were involved in the study. Overall, all farmers agreed that it was possible to apply the two products concurrently with minimal challenges. The trust on the safety of biolarvicides on both human and paddy health was high. Respondents reported no challenge in preparation and applying the product in their rice fields. Over half (56.6%) of the participants reported an average decrease in mosquito density in their households and a quarter (26.6%) of them reported a decrease in mosquito population in their farms. Similarly, 93.3% of the participants reported that the intervention had reduced malaria risk in their households. In general, all participants expressed willingness to contribute to a biolarvicide and fertilizer programme and to use the approach in their farming practices. Conclusion Community-based concurrent application of biolarvicides and fertilizer in rice fields was feasible and led to a perceived reduction in mosquito density. Willingness to pay for the larviciding/fertilizer approach was expressed by participants and they accepted to use the approach in their future farming practices. However, the impact of this approach on malaria transmission and rice grain harvest need to be evaluated in a large-scale programme.

Maps of infection risk are a vital tool for the elimination of malaria. Routine surveillance data of malaria case counts, often aggregated over administrative regions, is becoming more widely available and can better measure low malaria risk than prevalence surveys. However, aggregation of case counts over large, heterogeneous areas means that these data are often underpowered for learning relationships between the environment and malaria risk. A model that combines point surveys and aggregated surveillance data could have the benefits of both but must be able to account for the fact that these two data types are different malariometric units. Here, we train multiple machine learning models on point surveys and then combine the predictions from these with a geostatistical disaggregation model that uses routine surveillance data. We find that, in tests using data from Colombia and Madagascar, using a disaggregation regression model to combine predictions from machine learning models trained on point surveys improves model accuracy relative to using the environmental covariates directly.

Background During the past six decades, remarkable success on malaria control has been made in China. The major experience could be shared with other malaria endemic countries including Tanzania with high malaria burden. Especially, China’s 1–3-7 model for malaria elimination is one of the most important refined experiences from many years’ efforts and key innovation measures for malaria elimination in China. Methods The China-UK-Tanzania pilot project on malaria control was implemented from April, 2015 to June, 2018, which was an operational research with two communities receiving the proposed interventions and two comparable communities serving as control sites. The World Health Organization “Test, Treat, Track” (WHO-T3) Initiative, which calls for every suspected case to receive a diagnostic test, every confirmed case to be treated, and for the disease to be tracked, was integrated with Chinese experiences on malaria control and elimination for exploration of a proper model tailored to the local settings. Application of China’s 1–3-7 model integrating with WHO-T3 initiative and local resources aiming at reducing the burden of malaria in terms of morbidity and mortality by 30% in the intervention communities in comparison with that at the baseline survey. Discussion The China-UK-Tanzania pilot project on malaria control was that at China's first pilot project on malaria control in Africa, exploring the feasibility of Chinese experiences by China-Africa collaboration, which is expected that the strategies and approaches used in this project could be potential for scaling up in Tanzania and African countries, and contribute to the acceleration of malaria control and elimination in Africa. Electronic supplementary material The online version of this article (10.1186/s40249-018-0507-3) contains supplementary material, which is available to authorized users.

Background: Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. Methods: We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. Findings: We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000–17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8–277·7) to 193·9 million (156·6–240·2) and deaths declined from 925 800 (596 900–1 341 100) to 618 700 (368 600–952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. Interpretation: High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period.

Introduction:skill mix refers to the range of professional development and competencies, skills and experiences of staff within a particular working environment that link with specific outcome while responding to client needs. A balanced skill-mix and distribution of core human resources is important to strengthen decision-making process and rapid responses. We analysed graduates´ information of the Tanzania Field Epidemiology and Laboratory Training Program (TFELTP) between 2008-2016, distribution of skill-mix and the surveillance workforce-gaps within regions. Methods:trainees´ data of nine cohorts enrolled between 2008 and 2016 were extracted from the program database. Distribution by sex, region and cadres/profession was carried out. An indicator to determine enhanced-skill mix was established based on the presence of a clinician, nurse, laboratory scientist and environmental health officer. A complete enhanced skill-mix was considered when all four were available and have received FELTP training. Results:the TFELTP has trained 113 trainees (male=71.7%), originated from 17 regions of Tanzania Mainland (65.4% of all) and Zanzibar. Clinicians (34.5%) and laboratory scientists (38.1%) accounted for the most recruits, however, the former were widely spread in regions (83% vs. 56%). Environmental health officers (17.7%) were available in 39% of regions. The nursing profession, predominantly lacking (6.2%) was available in 22% of regions. Only two regions (11.7%) among 17 covered by TFELTP presented complete skill-mix, representing 7.7% of Tanzanian regions. Seven regions (41%) had an average of one trainee. Conclusion:the TFELTP is yet to reach the required skill-mix in many regions within the country. The slow fill-rate for competent and key workforce cadres might impede effective response. Strategies to increase program awareness at subnational levels is needed to improve performance of surveillance and response system in Tanzania.

We investigated a dengue outbreak in Dar es Salaam, Tanzania, in 2014, that was caused by dengue virus (DENV) serotype 2. DENV infection was present in 101 (20.9%) of 483 patients. Patient age and location of residence were associated with infection. Seven (4.0%) of 176 patients were co-infected with malaria and DENV.

Over the past decade, two movements have profoundly changed the environment in which global health epidemiologists work: research integrity and research fairness. Both ought to be equally nurtured by global health epidemiologists who aim to produce high quality impactful research. Yet bridging between these two aspirations can lead to practical and ethical dilemmas. In the light of these reflections we have proposed the BRIDGE guidelines for the conduct of fair global health epidemiology, targeted at stakeholders involved in the commissioning, conduct, appraisal and publication of global health research. The guidelines follow the conduct of a study chronologically from the early stages of study preparation until the dissemination and communication of findings. They can be used as a checklist by research teams, funders and other stakeholders to ensure that a study is conducted in line with both research integrity and research fairness principles. In this paper we offer a detailed explanation for each item of the BRIDGE guidelines. We have focused on practical implementation issues, making this document most of interest to those who are actually conducting the epidemiological work.

Background Folic acid fortification of staple foods has been in place in many countries for over two decades. Studies have shown that folic acid fortification can significantly reduce incidence of neural tube defects. Tanzania adopted a mandatory fortification policy for commercially-produced wheat and maize flour in 2011. We determined factors influencing intake of folic acid-fortified flour among women of reproductive age (WRA). Methods We conducted a cross-sectional study among WRA during March–April 2017 in Ifakara Town Council, Morogoro region. Multistage cluster sampling was used to select study participants. We used a questionnaire to capture information on demographics, awareness of folic acid, awareness of existence of folic acid fortified flour in community and intake of folic acid fortified flour. Intake was defined as reported consumption of folic acid fortified flour products at least once within 7 days before interview. Univariate, bivariate, and multivariable logistic analyses were done to evaluate factors associated with intake of folic acid fortified flour. Results The median age of the 698 participating WRA was 30 years (range: 18–49). Awareness of folic acid and folic acid fortified flour was 6.9% (95% CI: 5.2–9.0%) and 7.5% (95% CI: 5.7–9.6%), respectively. Consumption of folic acid fortified flour was 63.3% (95% CI: 59.7–66.8%). Independent factors associated with intake included being employed (aOR = 1.91; 95% CI: 1.19–3.06), having no children (nulliparity) (aOR = 2.59; 95% CI: 1.36–4.95) or having 1–4 children (aOR = 1.98; 95% CI: 1.17–3.33) (vs. 5 or more children), and folic acid awareness (aOR = 2.53; 95% CI: 1.30–4.92). Conclusion Folic acid fortified flour was used by most respondents in our study despite low awareness of existence of folic acid fortified flour in the community. Being employed, having fewer than five children, and folic acid awareness were independent factors associated with intake. We recommend scaling up of mandatory flour fortification program and doing further studies on blood folate level among women of reproductive age in Ifakara to assess fortification program effectiveness.

Background: In recent years, the eastern coast of Africa has witnessed a number of dengue outbreaks. This study was carried out to determine socio-demographic determinants of dengue infection during the 2014 outbreak in Dar es Salaam, Tanzania. Methods: Unmatched case-control analysis of secondary data from a cross-sectional dengue investigation in three districts of Dar es Salaam in June 2014 was conducted. Febrile patients seeking care at health facilities were recruited. Cases were serologically-confirmed dengue-positive while controls were serologically-confirmed dengue-negative patients. A questionnaire was used to collect sociodemographic information. The association between sociodemographic variables and dengue infection was examined using univariate analysis and multivariate logistic regression analysis. Results: A total of 81 cases and 281 controls were included in the analysis. Majority of the cases and controls were males (64.2% versus 54.1%; P=0.137) and were > 15 years of age (88.9% versus 72.9%; P =0.003). Living in Kinondoni (aOR = 4.28; 95% CI: 1.74 - 10.53); being employed (aOR = 2.06; 95% CI: 1.06-4.04); having piped water at home (aOR = 2.63; 95% CI: 1.40 - 4.95) and a recent visit of health facility (aOR = 1.94; 95% CI: 1.11 - 3.38) were significantly associated with dengue infection. Conclusions: Dengue infection in Dar es Salaam varied between the three districts and was associated with being employed, having piped water at home and a recent visit to the health facility. These findings provide primary understanding of the influence of socio-demographic factors on dengue and may be used to develop appropriate preventive interventions.

Background Understanding the causes of inpatient mortality in hospitals is important for monitoring the population health and evidence-based planning for curative and public health care. Dearth of information on causes and trends of hospital mortality in most countries of Sub-Saharan Africa has resulted to wide use of model-based estimation methods which are characterized by estimation errors. This retrospective analysis used primary data to determine the cause-specific mortality patterns among inpatient hospital deaths in Tanzania from 2006-2015. Materials and methods The analysis was carried out from July to December 2016 and involved 39 hospitals in Tanzania. A review of hospital in-patient death registers and report forms was done to cover a period of 10 years. Information collected included demographic characteristics of the deceased and immediate underlying cause of death. Causes of death were coded using international classification of diseases (ICD)-10. Data were analysed to provide information on cause-specific, trends and distribution of death by demographic and geographical characteristics. Principal findings A total of 247,976 deaths were captured over a 10-year period. The median age at death was 30 years, interquartile range (IQR) 1, 50. The five leading causes of death were malaria (12.75%), respiratory diseases (10.08%), HIV/AIDS (8.04%), anaemia (7.78%) and cardio-circulatory diseases (6.31%). From 2006 to 2015, there was a noted decline in the number of deaths due to malaria (by 47%), HIV/AIDS (28%) and tuberculosis (26%). However, there was an increase in number of deaths due to neonatal disorders by 128%. Malaria and anaemia killed more infants and children under 5 years while HIV/AIDS and Tuberculosis accounted for most of the deaths among adults. Conclusion The leading causes of inpatient hospital death were malaria, respiratory diseases, HIV/AIDS, anaemia and cardio-circulatory diseases. Death among children under 5 years has shown an increasing trend. The observed trends in mortality indicates that the country is lagging behind towards attaining the global and national goals for sustainable development. The increasing pattern of respiratory diseases, cancers and septicaemia requires immediate attention of the health system.

Background A nationwide, school, malaria survey was implemented to assess the risk factors of malaria prevalence and bed net use among primary school children in mainland Tanzania. This allowed the mapping of malaria prevalence at council level and assessment of malaria risk factors among school children. Methods A cross-sectional, school, malaria parasitaemia survey was conducted in 25 regions, 166 councils and 357 schools in three phases: (1) August to September 2014; (2) May 2015; and, (3) October 2015. Children were tested for malaria parasites using rapid diagnostic tests and were interviewed about household information, parents’ education, bed net indicators as well as recent history of fever. Multilevel mixed effects logistic regression models were fitted to estimate odds ratios of risk factors for malaria infection and for bed net use while adjusting for school effect. Results In total, 49,113 children were interviewed and tested for malaria infection. The overall prevalence of malaria was 21.6%, ranging from

This study was carried out to understand the role social determinants and health seeking behavior among rice farming and pastoral communities in Kilosa District in central Tanzania. The study involved four villages; two with rice farming communities while the other two with pastoral communities. In each village, heads of households or their spouses were interviewed to seek information on livelihoods activities, knowledge and practices on malaria and its preventions. A total of 471 individuals (males=38.9%; females=61.1%) were interviewed. Only 23.5% of the respondents had adequate knowledge on malaria. Fifty-six percent of the respondents could not associate any livelihood activity with malaria transmission. Majority (79%) of the respondents believed that most of fevers were due to malaria; this was higher among the pastoral (81.7%) than rice farming communities (76.1%) (p=0.038). Cases of fever were significantly higher in households with non-educated (31.2%) than educated respondents (21.5%). Women experienced significantly more episodes of fever than men (p

Background: Since 2001, Tanzania has been making concerted efforts to strengthen its Integrated Disease Surveillance and Response system. In this system, malaria is one of the priority diseases that are to be reported monthly. The objectives of this study were to (i) assess malaria surveillance system at facility and district levels to identify key barriers, constraints and priority actions for malaria surveillance strengthening; and (ii) to explore the use of evidence in health planning and decision making at these levels.Methods: The study was carried in Kilosa District in central Tanzania, during October 2012 and involved health facility workers and members of the district health management team. The existing information system on malaria was evaluated using a structured questionnaire and check list. Data collection also involved direct observations of reporting and processing, assessment of report forms and reports of processed data.Results: Three district officials and 17 health facility workers from both public and private health facilities were interviewed. Of the 17 informants, 15 were familiar with disease surveillance functions. A good percentage (47%, 8/17) received training on disease surveillance during the previous two years. Public transport and motorcycles were the main means of reporting epidemiological information from facility to district level. Most of the health facilities (93%, 14/15) faced difficulties in submitting reports due to lack of resources and feedback from the district authority. Analysis of malaria data was reported in 52.9% (9/17) of the facilities, but limited to malaria incidence per age groups. Challenges in data analysis included unavailability of compilation books; lack of computers; poor data storage; incomplete recording; lack of adequate skills for data analysis; and increase in workloads. Data at both facility and district levels were mainly used for quantification and forecasting of drug requirements.Conclusion: Malaria surveillance system in Kilosa district is weak and utilization of evidence for planning and decision making is poor. Capacity strengthening on data analysis and utilization should be given a priority at both facility and district levels of the health systems in Tanzania.

Ethnopharmacological relevance Indigenous community of Mkuranga district have been using aqueous extract of H. sabdariffa L. for treating anemia. However, there have been neither safety nor efficacy studies to validate this medicinal product in anemia. Aim The purpose of this study was to establish efficacy and safety of standardized aqueous extract of H. sabdariffa L. in anemic adults. Materials and methods This was a randomized controlled clinical trial in which 130 adults’ men and women aged 18–50 years were involved after meeting the inclusion criteria. Initially, standardized aqueous extract of H. sabdariffa L. was prepared using optimized extraction parameters. Stratified randomization was used to randomize participants into four fixed dose groups. The first group received oral dose of 1000 ml while the 2nd group was randomized to receive 1500 ml orally. The last two groups were given a dose of 2000 ml of extract and 200 mg ferrous sulphate tablet respectively. Primary endpoint was the actual change of iron status indicators at the end of 30 days follow up period as compared to those recorded at baseline. Adverse effects were assessed at every 10th day scheduled visit. In all arms, HB and hematopoietic parameters were measured using HemoCue hemoglobinometer® (HemoCue, Angelholm, Sweden) and hematology analyzer® respectively at the trial site. Follow up was done for 30 days. A total of 82 participants were included for analysis. Results A standardized aqueous extract of H. sabdariffa L. did not improve iron status in anemic adults in malaria endemic region (P>0.005). However, there was evidence to support the safety of the extract for human consumptions as herbal supplement. Iron and organic acids contents of H. sabdariffa L. extract showed the potential of improving hematopoietic parameters. Studies with bigger sample size are therefore needed to establish the efficacy of the extract when concurrently used with malaria chemoprophylaxis in malaria endemic areas.

In 2009, the Tanzanian Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) counted over 10 different health facility lists managed by donors, government ministries, agencies and implementing partners. These function-specific lists were not integrated or linked. The ministry's Health Sector Strategic Plan included the development of an authoritative source for all health facility information, called the Master Facility List (MFL). During development, the ministry adopted the term Health Facility Registry (HFR), an online tool providing public access to a database about all officially recognized health facilities (public and private). The MFL, which includes the health facility list at any specific point in time can be exported from the HFR. This chapter presents the Tanzanian case study describing the work and lessons learned in building the HFR—focusing on software development, introducing geographic positioning systems and harmonizing MFL data. MoHCDGEC launched the HFR public portal in September 2015.

BackgroundMaternal mortality is among the most important public health concerns in Sub-Saharan Africa. There is limited data on hospital-based maternal mortality in Tanzania. The objective of this study was to determine the causes and maternal mortality trends in public hospitals of Tanzania from 2006-2015.Methods and findingsThis retrospective study was conducted between July and December 2016 and involved 34 public hospitals in Tanzania. Information on causes of deaths due to pregnancy and delivery complications among women of child-bearing age (15-49 years old) recorded for the period of 2006-2015 was extracted. Data sources included inpatient and death registers and International Classification of Disease (ICD)-10 report forms. Maternal deaths were classified based on case definition by ICD 10 and categorized as direct and indirect causes. A total of 40,052 deaths of women of child-bearing age were recorded. There were 1,987 maternal deaths representing 5·0% of deaths of all women aged 15-49 years. The median age-at-death was 27 years (interquartile range: 22, 33). The average age-at-death increased from 25 years in 2006 to 29 years in 2015. Two thirds (67.1%) of the deaths affected women aged 20-34 years old. The number of deaths associated with teenage pregnancy (15-19 years) declined significantly (p-valueConclusionsDuring the ten year period (2006-2015) there was an increase in the number of hospital maternal deaths in public hospitals in Tanzania. Maternal deaths accounted for 5% of all women of child-bearing age in-hospital mortalities. Most maternal deaths were due to direct causes including eclampsia, haemorrhage and sepsis. The findings of this study provide evidence for better planning and policy formulation for reproductive health programmes to reduce maternal deaths in Tanzania.

There is a paucity of research on micro-level assessment of the dynamics of socio-economic status following health interventions. The use of household asset data to determine wealth indices is a common procedure for estimating socio-economic position in low-income countries. Indeed, in such settings information about income is usually lacking and the collection of individual consumption or expenditure data would require in-depth interviews, posing a considerable risk of bias. In this study, we determined the socio-economic status of 159 households in a village in north-western Tanzania before and 1 year after participatory hygiene and sanitation transformation (PHAST) intervention to control schistosomiasis. We constructed a household 'wealth index' based on durable assets ownership (e.g. bicycle and radio) and household characteristics dealing with ownership of land and house construction features (e.g. type of walls and roof). We employed principal components analysis and classified households into wealth quintiles. The study revealed that asset variables with positive factor scores were associated with higher socio-economic status, whereas asset variables with negative factor scores were associated with lower socio-economic status. Overall, households which were rated as the poorest and very poor were on the decrease, whereas those rated as poor, less poor and the least poor were on the increase after PHAST intervention. This decrease/increase was significant. The median shifted from -0.761 to -0.448, and the mean from -0.204 (standard deviation (SD) 1.924) to 0.193 (SD 2.079) between pre- and post-intervention phases. The difference in socio-economic status of the people comparing the pre- and post-intervention phases was highly statistically significant (p>0.001). This observation was confirmed by a multinomial model with a random effect on the households. We argue that significant changes in the socio-economic status observed in our study are attributable to the PHAST intervention, despite other sporadic interventions against schistosomiasis.

Lack of birth and death registries in most of developing countries, particularly those in sub-Saharan Africa led to the establishment of Demographic Surveillance Systems (DSS) sites which monitor large population cohorts within defined geographical areas. DSS collects longitudinal data on migration, births, deaths and their causes via verbal autopsies. DSS data provide an opportunity to monitor many health indicators including mortality trends. Mortality rates in Sub-Sahara Africa show seasonal patterns due to high infant and child malaria-related mortality which is influenced by seasonal features present in environmental and climatic factors. However, it is unclear whether seasonal patterns differ by age in the first few months of life. This study provides an overview of approaches to assess, capture and detect seasonality peaks and patterns in mortality using the infant mortality data from the Rufiji DSS, Tanzania. Seasonality was best captured using Bayesian negative binomial models with time and cycle dependent seasonal parameters and autoregressive temporal error terms. Seasonal patterns are similar among different age groups during infancy and timing of their mortality peaks do not differ. Seasonality in mortality rates with two peaks per year is pronounced which corresponds to rainy seasons. Understanding of these trends is important for public health preparedness.