Update to: A stakeholder workshop about modelled maps of key malaria indicator survey indicators in Madagascar.
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SUBMITTER: Howes RE
PROVIDER: S-EPMC6953134 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Update to: A stakeholder workshop about modelled maps of key malaria indicator survey indicators in Madagascar.
Howes Rosalind E RE Hawa Kaleem K Andriamamonjy Voahangy Fanomezana VF Franchard Thierry T Miarimbola Raharizo R Mioramalala Sedera Aurélien SA Rafamatanantsoa Jean Florent JF Rahantamalala Mirana Ando Mbolatiana MAM Rajaobary Solo Harimalala SH Rajaonera Hariniaina David Gaël HDG Rakotonindrainy Andrianiaina Parfait AP Andrianjatonavalona Clairaut Rakotoson CR Randriamiarinjatovo Dina Ny Aina Liantsoa DNAL Randrianasolo Faratiana Michèle FM Razafindratovo Rado Malalatiana Ramasy RMR Ravaoarimanga Masiarivony M Ye Maurice M Gething Peter W PW Taylor Cameron A CA
Malaria journal 20200109 1
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Project description:BackgroundManaged problem solving (MAPS) is an evidence-based intervention that can boost HIV medication adherence and increase viral suppression, but it is not widely used in community clinics. Deploying community health workers to deliver MAPS could facilitate broader implementation, in support of the Ending the HIV Epidemic (EHE) initiative's goal of reducing new HIV infections in the US by 90% by 2030.SettingRyan White-funded clinics in Philadelphia, 1 of 48 US counties prioritized in the EHE.MethodsSemistructured stakeholder interviews were conducted with 13 clinics and 4 stakeholder groups: prescribing clinicians, nonprescribing clinical team members (eg, medical case managers), clinic administrators, and policymakers. Interviews were based on the Consolidated Framework for Implementation Research and investigated perceived barriers to and facilitators of MAPS delivery by community health workers. Rapid qualitative analytic techniques were used to synthesize interview data and identify key categories along an implementation pathway. Core determinants (ie, barriers and facilitators) of MAPS implementation were grouped within each category.ResultsStakeholders were receptive to CHW-delivered MAPS and offered critical information on potential implementation determinants including preferences for identification and referral of patients, and the importance of integration and communication within the care team.ConclusionsThis study elucidates insights regarding barriers and facilitators to delivering an evidence-based behavioral intervention in clinics serving people with HIV (PWH) and extends a rapid qualitative approach to HIV care that rigorously incorporates stakeholder data into the development of implementation strategies. It also offers insights for national implementation efforts associated with EHE.
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Project description:BackgroundDespite a relatively good national case reporting system in Sri Lanka, detailed maps of malaria distribution have not been publicly available.MethodsIn this study, monthly records over the period 1995 - 2000 of microscopically confirmed malaria parasite positive blood film readings, at sub-district spatial resolution, were used to produce maps of malaria distribution across the island. Also, annual malaria trends at district resolution were displayed for the period 1995 - 2002.ResultsThe maps show that Plasmodium vivax malaria incidence has a marked variation in distribution over the island. The incidence of Plasmodium falciparum malaria follows a similar spatial pattern but is generally much lower than that of P. vivax. In the north, malaria shows one seasonal peak in the beginning of the year, whereas towards the south a second peak around June is more pronounced.ConclusionThis paper provides the first publicly available maps of both P. vivax and P. falciparum malaria incidence distribution on the island of Sri Lanka at sub-district resolution, which may be useful to health professionals, travellers and travel medicine professionals in their assessment of malaria risk in Sri Lanka. As incidence of malaria changes over time, regular updates of these maps are necessary.
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Project description:BACKGROUND:There are various complex reasons that influence sustainable adoption of innovations in health care systems. Low adoption can be caused by a lack of support from one or more stakeholders because their needs and expectations are not always considered or aligned. OBJECTIVE:This study aimed to identify stakeholders' perceptions of barriers and facilitators toward the sustainable adoption of digital health innovations. METHODS:A stakeholder workshop was attended by 12 participants with a range of backgrounds on August 25, 2017, including people representing the views from patients, carers, local hospitals, pharmacy retailers, health insurers, health services researchers, engineers, and technology and pharmaceutical companies in Switzerland. On the basis of adoption of innovation frameworks, we asked participants to interview each other about 3 factors influencing the adoption of digitally delivered health interventions: (1) Facilitators and barriers in the external system, (2) Needs and expectations of stakeholders, and (3) Safety, quality, and usability of innovations. The worksheets and videos generated from the workshop were qualitatively analyzed and summarized. RESULTS:Facilitators for adoption mentioned were high levels of income and education, and digital health is a high priority to stakeholders. Main common interests of different stakeholders were patient satisfaction and job protection. Health care spending was a misaligned interest: although some stakeholders were keen on spending more to obtain or provide the highest quality of care, others were focused on reducing health care spending to provide cost-effective services. Switzerland's diversity and complexity, in terms of its organization with 26 cantons (administrative divisions), were barriers as these made it harder to ensure interoperability of interventions. A culture of innovation was considered a push factor, but adoption was inhibited by persistent paper-based systems, a fear of change, and unwillingness to share data. The sustainability of interventions can be promoted by making them patient-centered, meaning that patients should be involved throughout their development. CONCLUSIONS:Promoting sustainable adoption of digital health remains challenging despite various push factors being in place. Barriers related to fragmentation, patient-centeredness, data security, privacy, trust, and job security need to be addressed. A strength is that people from a wide range of backgrounds attended the workshop. A limitation is that the findings are focused on the macro level. In-depth case studies of specific issues need to be conducted in different settings.
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Project description:The commonly used validation metrics for the local agreement of a structure model with the observed electron density, namely the real-space R (RSR) and the real-space correlation coefficient (RSCC), are reviewed. It is argued that the primary goal of all validation techniques is to verify the accuracy of the model, since precision is an inherent property of the crystal and the data. It is demonstrated that the principal weakness of both of the above metrics is their inability to distinguish the accuracy of the model from its precision. Furthermore, neither of these metrics in their usual implementation indicate the statistical significance of the result. The statistical properties of electron-density maps are reviewed and an improved alternative likelihood-based metric is suggested. This leads naturally to a χ(2) significance test of the difference density using the real-space difference density Z score (RSZD). This is a metric purely of the local model accuracy, as required for effective model validation and structure optimization by practising crystallographers prior to submission of a structure model to the PDB. A new real-space observed density Z score (RSZO) is also proposed; this is a metric purely of the model precision, as a substitute for other precision metrics such as the B factor.
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Project description:BACKGROUND:Malaria is one of the primary health concerns in Madagascar. Based on the duration and intensity of transmission, Madagascar is divided into five epidemiological strata that range from low to mesoendemic transmission. In this study, the spatial and temporal dynamics of malaria within each epidemiological zone were studied. METHODS:The number of reported cases of uncomplicated malaria from 112 health districts between 2010 and 2014 were compiled and analysed. First, a Standardized Incidence Ratio was calculated to detect districts with anomalous incidence compared to the stratum-level incidence. Building on this, spatial and temporal malaria clusters were identified throughout the country and their variability across zones and over time was analysed. RESULTS:The incidence of malaria increased from 2010 to 2014 within each stratum. A basic analysis showed that districts with more than 50 cases per 1000 inhabitants are mainly located in two strata: East and West. Lower incidence values were found in the Highlands and Fringe zones. The standardization method revealed that the number of districts with a higher than expected numbers of cases increased through time and expanded into the Highlands and Fringe zones. The cluster analysis showed that for the endemic coastal region, clusters of districts migrated southward and the incidence of malaria was the highest between January and July with some variation within strata. CONCLUSION:This study identified critical districts with low incidence that shifted to high incidence and district that were consistent clusters across each year. The current study provided a detailed description of changes in malaria epidemiology and can aid the national malaria programme to reduce and prevent the expansion of the disease by targeting the appropriate areas.
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Project description:BackgroundRoutine Health Information Systems (RHIS) are important for not just sure enough control of malaria, but its elimination as well. If these systems are working, they can extensively provide accurate data on reported malaria cases instead of presenting modelled approximations of malaria burden. Queries are raised on both the quality and use of generated malaria data. Some issues of concern include inaccurate reporting of malaria cases as well as treatment plans, wrongly categorizing malaria cases in registers used to collate data and misplacing data or registers for reporting. This study analyses data quality concerning health staff's proficiency, timeliness, availability and data accuracy in the Sissala East Municipal Health Directorate (MHD).MethodsA cross-sectional design was used to collect data from 15 facilities and 50 health staff members who offered clinical related care for malaria cases in the Sissala East MHD from 24th August 2020 to 17th September 2020. Fifteen health facilities were randomly selected from the 56 health facilities in the municipality that were implementing the malarial control programme, and they were included in the study.ResultsOn the question of when did staff receive any training on malaria-related health information management in the past six months prior to the survey, as minimal as 13 out of 50(26%) claimed to have been trained, whereas the majority 37 out of 50 (74%) had no training. In terms of proficiency in malaria indicators (MI), the majority (68% - 82%) of the respondents could not demonstrate the correct calculations of the indicators. Nevertheless, the MHD recorded monthly average timeliness of the 5th day [range: 4.7-5.7] within the reporting year. However, the MHD had a worse average performance of 5.4th and 5.7th days in July and September respectively. Furthermore, results indicated that 14 out of 15(93.3%) facilities exceeded the target to accomplish report availability (> = 90%) and data completeness (> = 90%). However, the verification factor (VF) of the overall malaria indicator showed that the MHD neither over-reported nor under-reported actual cases, with the corresponding level of data quality as Good (+/-5%).ConclusionsThe Majority of staff had not received any training on malaria-related RHIS. Some staff members did not know the correct definitions of some of MI used in the malaria programme, while the majority of them could not demonstrate the correct calculations of MI. Timeliness of reporting was below the target, nevertheless, copies of data that were submitted were available and completed. There should be training, supervision and monitoring to enhance staff proficiency and improve the quality of MI.
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Project description:Displaying Nitrogen (N) indicators on a global grid poses unique opportunities to quantify environmental impacts from N application in different world regions under a variety of conditions. Such calculations require the use of maps showing the geo-spatial distribution of crop production. Although there are several crop maps in the scientific literature to choose from, the consequences of this choice for the calculation of N indicators still need to be evaluated. In this study we analyze the differences in results for N Use Efficiency (NUE) and N surplus calculated on the global scale using two different crop maps (SPAM and M3). For our calculations we used publicly available statistical and literature data combined with each crop map and carefully traced the origins of the differences in the results. Our results showed that the regions most affected by discrepancies caused by differences in crop maps (yields and physical area) are Central Asia and the Russian Federation, Australia and Oceania, and North Africa. However, we also found that the inclusion or exclusion of grass crops influences the results, as does the aggregation of crops to categories. Considering all these differences, we note that M3 seems to provide the more plausible results for the calculation of N indicators. Our analysis not only highlights the importance of determining the critical parameters for N indicator calculation, but also allows key parameters connected with N use and overuse to be identified on the global scale.
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Project description:BackgroundStandardised care pathways tailored to women/couples who experience recurrent miscarriage are needed; however, clinical practice is inconsistent and poorly organised. In this paper, we outline our processes and experiences of developing guideline-based key performance indicators (KPIs) for recurrent miscarriage care with a diverse stakeholder group which will be used to evaluate national services. To date, such exercises have generally only involved clinicians, with the need for greater stakeholder involvement highlighted.MethodsOur study involved six stages: (i) identification and synthesis of recommendations for recurrent miscarriage care through a systematic review of clinical practice guidelines; (ii) a two-round modified e-Delphi survey with stakeholders to develop consensus on recommendations and outcomes; (iii) four virtual meetings to develop this consensus further; (iv) development of a list of candidate KPIs; (v) survey to achieve consensus on the final suite of KPIs and a (vi) virtual meeting to agree on the final set of KPIs. Through participatory methods, participants provided feedback on the process of KPI development.ResultsFrom an initial list of 373 recommendations and 14 outcomes, 110 indicators were prioritised for inclusion in the final suite of KPIs: (i) structure of care (n = 20); (ii) counselling and supportive care (n = 7); (iii) investigations (n = 30); treatment (n = 34); outcomes (n = 19). Participants' feedback on the process comprised three main themes: accessibility, richness in diversity, streamlining the development process.ConclusionsIt is important and feasible to develop guideline-based KPIs with a diverse stakeholder group. One hundred and ten KPIs were prioritised for inclusion in a suite of guideline-based KPIs for recurrent miscarriage care. Insights into our experiences may help others undertaking similar projects, particularly those undertaken in the absence of a clinical guideline and/or involving a range of stakeholders.
| S-EPMC9107009 | biostudies-literature
Project description:BackgroundMany 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.MethodsWith 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.ResultsPositive 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.ConclusionsMonthly 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.
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Project description:In areas where malaria epidemiology is spatially and temporally heterogeneous, human-mediated parasite importation can result in non-locally acquired clinical cases and outbreaks in low-transmission areas. Using mobility estimates derived from the mobile phone data and spatial malaria prevalence data, we identify travel routes relevant to malaria transmission in Madagascar. We find that the primary hubs of parasite importation are in a spatially connected area of the central highlands. Surprisingly, sources of these imported infections are not spatially clustered. We then related these source locations directly to clinical cases in the low-transmission area of the capital. We find that in the capital, a major sink, the primary sources of infection are along the more populated coastal areas, although these sources are seasonally variable. Our results have implications for targeting interventions at source locations to achieve local or national malaria control goals.
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