8 research outputs found

    The changes in health service utilisation in Malawi during the COVID-19 pandemic

    Get PDF
    Introduction The COVID-19 pandemic and the restriction policies implemented by the Government of Malawi may have disrupted routine health service utilisation. We aimed to find evidence for such disruptions and quantify any changes by service type and level of health care. Methods We extracted nationwide routine health service usage data for 2015–2021 from the electronic health information management systems in Malawi. Two datasets were prepared: unadjusted and adjusted; for the latter, unreported monthly data entries for a facility were filled in through systematic rules based on reported mean values of that facility or facility type and considering both reporting rates and comparability with published data. Using statistical descriptive methods, we first described the patterns of service utilisation in pre-pandemic years (2015–2019). We then tested for evidence of departures from this routine pattern, i.e., service volume delivered being below recent average by more than two standard deviations was viewed as a substantial reduction, and calculated the cumulative net differences of service volume during the pandemic period (2020–2021), in aggregate and within each specific facility. Results Evidence of disruptions were found: from April 2020 to December 2021, services delivered of several types were reduced across primary and secondary levels of care–including inpatient care (-20.03% less total interactions in that period compared to the recent average), immunisation (-17.61%), malnutrition treatment (-34.5%), accidents and emergency services (-16.03%), HIV (human immunodeficiency viruses) tests (-27.34%), antiretroviral therapy (ART) initiations for adults (-33.52%), and ART treatment for paediatrics (-41.32%). Reductions of service volume were greatest in the first wave of the pandemic during April-August 2020, and whereas some service types rebounded quickly (e.g., outpatient visits from -17.7% to +3.23%), many others persisted at lower level through 2021 (e.g., under-five malnutrition treatment from -15.24% to -42.23%). The total reduced service volume between April 2020 and December 2021 was 8 066 956 (-10.23%), equating to 444 units per 1000 persons. Conclusion We have found substantial evidence for reductions in health service delivered in Malawi during the COVID-19 pandemic which may have potential health consequences, the effect of which should inform how decisions are taken in the future to maximise the resilience of healthcare system during similar events

    Modeling Contraception and Pregnancy in Malawi : A Thanzi La Onse Mathematical Modeling Study

    Get PDF
    Malawi has high unmet need for contraception with a costed national plan to increase contraception use. Estimating how such investments might impact future population size in Malawi can help policymakers understand effects and value of policies to increase contraception uptake. We developed a new model of contraception and pregnancy using individual-level data capturing complexities of contraception initiation, switching, discontinuation, and failure by contraception method, accounting for differences by individual characteristics. We modeled contraception scale-up via a population campaign to increase initiation of contraception (Pop) and a postpartum family planning intervention (PPFP). We calibrated the model without new interventions to the UN World Population Prospects 2019 medium variant projection of births for Malawi. Without interventions Malawi's population passes 60 million in 2084; with Pop and PPFP interventions. it peaks below 35 million by 2100. We compare contraception coverage and costs, by method, with and without interventions, from 2023 to 2050. We estimate investments in contraception scale-up correspond to only 0.9 percent of total health expenditure per capita though could result in dramatic reductions of current pressures of very rapid population growth on health services, schools, land, and society, helping Malawi achieve national and global health and development goals

    Critical chain identication and buffer sizing for efficient project management

    No full text
    Project management organises about 30% of the world's economy (Hu et al., 2015b). Many recent projects apply critical chain project management (CCPM) methodology, which requires critical chain identification and design of project and feeding buffers. Critical chain identification is fundamental as it provides a baseline schedule without resource contentions. Subsequently, accurate sizing of the time buffers is essential, because too small buffers result in emergency procedures to prevent late delivery, whereas too large buffers result in uncompetitive bids and lost contracts. Previous research simply treats the former as a standard resource-constrained project scheduling problem (RCPSP) and predominantly focuses on the buffer sizing problem. The work typically results in excessive buffers and in critical chains being challenged by the insertion of feeding buffers, leading to inconsistent performance in project makespan estimation. In this research, we start with an explicit definition for the problem of critical chain identification considering how to deal with resource contentions. In addition to the RCPSP method that avoids concurrent processing of tasks involved, three new methods that allow for concurrent processing of tasks via trade-off between time and cost/resource are proposed and represented in mathematical programming models, which are actually generalised RCPSPs and potentially provide shorter critical chains and CCPM schedules. Then, heuristics are proposed to solve these NP-hard models. Experimental analysis on wide-ranging real-life project data confirms the effectiveness of these methods and tests the validity of the proposed heuristics against benchmarks. Given that the critical chain and baseline schedule are determined, we develop a new buffer sizing procedure based on analytical network decomposition. The procedure is implementable for any project network and offers logical advantages over previous ones. First, the size of a feeding buffer is determined from all associated noncritical chains. Second, the project buffer incorporates safety margins outside the critical chain by comparing feeding chains with their parallel critical counterparts. Computational testing on a case study of a real project and extensive simulated data shows that our procedure delivers much greater accuracy in estimating project makespan, and smaller feeding buffers. Furthermore, the resulting critical chain is never challenged. Additional benefits include delayed expenditure, and reductions in work-in-process, rework, and multitasking. Then, an improved CCPM method is obtained by combining the critical chain identification and buffer sizing procedures. We conduct a numerical study on the time performance of the CCPM compared to traditional critical path methods, using diverse real-life project data and considering different scenarios of uncertainties and risk preferences. The results indicate consistent advantages of CCPM regarding short and accurate project makespan estimates. Comprehensive information of how each method performs in each scenario is also provided to help with the decision making of appropriate scheduling techniques for any specified project. Overall, this research fundamentally improves the CCPM methodology to deliver efficient project schedules and provides clear guidelines for project managers to choose the right scheduling techniques for real-life projects

    Buffer sizing in critical chain project management by network decomposition

    No full text
    Project management organizes about 30% of the world's economy. Many recent projects apply critical chain project management (CCPM) methodology, which requires the design of project and feeding buffers. Accurate sizing of these buffers is essential, because too small buffers result in emergency procedures to prevent late delivery, whereas too large buffers result in uncompetitive bids and lost contracts. Previous buffer sizing research, focused predominantly on the critical chain, typically results in excessive buffers, and in critical chains being challenged by feeding buffers during planning. This work also performs inconsistently, for example in makespan estimation, at execution. We propose a new procedure for buffer sizing based on network decomposition, which offers logical advantages over previous ones. First, the size of a feeding buffer is determined from all associated noncritical chains. Second, the project buffer incorporates safety margins outside the critical chain by comparing feeding chains with their parallel critical counterparts. Computational testing on a case study of a real project and extensive simulated data shows that our procedure delivers much greater accuracy in estimating project makespan, and smaller feeding buffers. Furthermore, the resulting critical chain is never challenged. Additional benefits include delayed expenditure, and reductions in work-in-process, rework, and multitasking

    The Thanzi La Onse Model

    No full text
    Our fundamental aim is to develop the use of epidemiological and economic science to effect a step-change in the way that health priorities are addressed through policy interventions in low-income countries. We are doing this by developing a model that represents explicitly the generation of health gains in a population, which can be used to examine the effect of resource allocation, management and clinical practice, in order to contribute to informing decision-making.If you use this software, please cite it using the metadata from this file

    Estimating the health burden of road traffic injuries in Malawi using an individual-based model

    Get PDF
    Background: Road traffic injuries are a significant cause of death and disability globally. However, in some countries the exact health burden caused by road traffic injuries is unknown. In Malawi, there is no central reporting mechanism for road traffic injuries and so the exact extent of the health burden caused by road traffic injuries is hard to determine. A limited number of models predict the incidence of mortality due to road traffic injury in Malawi. These estimates vary greatly, owing to differences in assumptions, and so the health burden caused on the population by road traffic injuries remains unclear. Methods: We use an individual-based model and combine an epidemiological model of road traffic injuries with a health seeking behaviour and health system model. We provide a detailed representation of road traffic injuries in Malawi, from the onset of the injury through to the final health outcome. We also investigate the effects of an assumption made by other models that multiple injuries do not contribute to health burden caused by road accidents. Results: Our model estimates an overall average incidence of mortality between 23.5 and 29.8 per 100,000 person years due to road traffic injuries and an average of 180,000 to 225,000 disability-adjusted life years (DALYs) per year between 2010 and 2020 in an estimated average population size of 1,364,000 over the 10-year period. Our estimated incidence of mortality falls within the range of other estimates currently available for Malawi, whereas our estimated number of DALYs is greater than the only other estimate available for Malawi, the GBD estimate predicting and average of 126,200 DALYs per year over the same time period. Our estimates, which account for multiple injuries, predict a 22–58% increase in overall health burden compared to the model ran as a single injury model. Conclusions: Road traffic injuries are difficult to model with conventional modelling methods, owing to the numerous types of injuries that occur. Using an individual-based model framework, we can provide a detailed representation of road traffic injuries. Our results indicate a higher health burden caused by road traffic injuries than previously estimated

    Factors associated with medical consumable availability in level 1 facilities in Malawi : a secondary analysis of a facility census

    Get PDF
    BACKGROUND: Medical consumable stock-outs negatively affect health outcomes not only by impeding or delaying the effective delivery of services but also by discouraging patients from seeking care. Consequently, supply chain strengthening is being adopted as a key component of national health strategies. However, evidence on the factors associated with increased consumable availability is limited. METHODS: In this study, we used the 2018-19 Harmonised Health Facility Assessment data from Malawi to identify the factors associated with the availability of consumables in level 1 facilities, ie, rural hospitals or health centres with a small number of beds and a sparsely equipped operating room for minor procedures. We estimate a multilevel logistic regression model with a binary outcome variable representing consumable availability (of 130 consumables across 940 facilities) and explanatory variables chosen based on current evidence. Further subgroup analyses are carried out to assess the presence of effect modification by level of care, facility ownership, and a categorisation of consumables by public health or disease programme, Malawi's Essential Medicine List classification, whether the consumable is a drug or not, and level of average national availability. FINDINGS: Our results suggest that the following characteristics had a positive association with consumable availability-level 1b facilities or community hospitals had 64% (odds ratio [OR] 1·64, 95% CI 1·37-1·97) higher odds of consumable availability than level 1a facilities or health centres, Christian Health Association of Malawi and private-for-profit ownership had 63% (1·63, 1·40-1·89) and 49% (1·49, 1·24-1·80) higher odds respectively than government-owned facilities, the availability of a computer had 46% (1·46, 1·32-1·62) higher odds than in its absence, pharmacists managing drug orders had 85% (1·85, 1·40-2·44) higher odds than a drug store clerk, proximity to the corresponding regional administrative office (facilities greater than 75 km away had 21% lower odds [0·79, 0·63-0·98] than facilities within 10 km of the district health office), and having three drug order fulfilments in the 3 months before the survey had 14% (1·14, 1·02-1·27) higher odds than one fulfilment in 3 months. Further, consumables categorised as vital in Malawi's Essential Medicine List performed considerably better with 235% (OR 3·35, 95% CI 1·60-7·05) higher odds than other essential or non-essential consumables and drugs performed worse with 79% (0·21, 0·08-0·51) lower odds than other medical consumables in terms of availability across facilities. INTERPRETATION: Our results provide evidence on the areas of intervention with potential to improve consumable availability. Further exploration of the health and resource consequences of the strategies discussed will be useful in guiding investments into supply chain strengthening. FUNDING: UK Research and Innovation as part of the Global Challenges Research Fund (Thanzi La Onse; reference MR/P028004/1), the Wellcome Trust (Thanzi La Mawa; reference 223120/Z/21/Z), the UK Medical Research Council, the UK Department for International Development, and the EU (reference MR/R015600/1)
    corecore