Assessing the effect of health system resources on HIV and tuberculosis programmes in Malawi: a modelling study.

BACKGROUND: Malawi is progressing towards UNAIDS and WHO End TB Strategy targets to eliminate HIV/AIDS and tuberculosis. We aimed to assess the prospective effect of achieving these goals on the health and health system of the country and the influence of consumable constraints. METHODS: In this modelling study, we used the Thanzi la Onse (Health for All) model, which is an individual-based multi-disease simulation model that simulates HIV and tuberculosis transmission, alongside other diseases (eg, malaria, non-communicable diseases, and maternal diseases), and gates access to essential medicines according to empirical estimates of availability. The model integrates dynamic disease modelling with health system engagement behaviour, health system use, and capabilities (ie, personnel and consumables). We used 2018 data on the availability of HIV and tuberculosis consumables (for testing, treatment, and prevention) across all facility levels of the country to model three scenarios of HIV and tuberculosis programme scale-up from Jan 1, 2023, to Dec 31, 2033: a baseline scenario, when coverage remains static using existing consumable constraints; a constrained scenario, in which prioritised interventions are scaled up with fixed consumable constraints; and an unconstrained scenario, in which prioritised interventions are scaled up with maximum availability of all consumables related to HIV and tuberculosis care. FINDINGS: With uninterrupted medical supplies, in Malawi, we projected HIV and tuberculosis incidence to decrease to 26 (95% uncertainty interval [UI] 19-35) cases and 55 (23-74) cases per 100 000 person-years by 2033 (from 152 [98-195] cases and 123 [99-160] cases per 100 000 person-years in 2023), respectively, with programme scale-up, averting a total of 12·21 million (95% UI 11·39-14·16) disability-adjusted life-years. However, the effect was compromised by restricted access to key medicines, resulting in approximately 58 700 additional deaths (33 400 [95% UI 22 000-41 000] due to AIDS and 25 300 [19 300-30 400] due to tuberculosis) compared with the unconstrained scenario. Between 2023 and 2033, eliminating HIV treatment stockouts could avert an estimated 12 100 deaths compared with the baseline scenario, and improved access to tuberculosis prevention medications could prevent 5600 deaths in addition to those achieved through programme scale-up alone. With programme scale-up under the constrained scenario, consumable stockouts are projected to require an estimated 14·3 million extra patient-facing hours between 2023 and 2033, mostly from clinical or nursing staff, compared with the unconstrained scenario. In 2033, with enhanced screening, 188 000 (81%) of 232 900 individuals projected to present with active tuberculosis could start tuberculosis treatment within 2 weeks of initial presentation if all required consumables were available, but only 8600 (57%) of 15 100 presenting under the baseline scenario. INTERPRETATION: Ignoring frailties in the health-care system, in particular the potential non-availability of consumables, in projections of HIV and tuberculosis programme scale-up might risk overestimating potential health impacts and underestimating required health system resources. Simultaneous health system strengthening alongside programme scale-up is crucial, and should yield greater benefits to population health while mitigating the strain on a heavily constrained health-care system. FUNDING: Wellcome and UK Research and Innovation as part of the Global Challenges Research Fund.

A new approach to Health Benefits Package design: an application of the Thanzi La Onse model in Malawi.

An efficient allocation of limited resources in low-income settings offers the opportunity to improve population-health outcomes given the available health system capacity. Efforts to achieve this are often framed through the lens of "health benefits packages" (HBPs), which seek to establish which services the public healthcare system should include in its provision. Analytic approaches widely used to weigh evidence in support of different interventions and inform the broader HBP deliberative process however have limitations. In this work, we propose the individual-based Thanzi La Onse (TLO) model as a uniquely-tailored tool to assist in the evaluation of Malawi-specific HBPs while addressing these limitations. By mechanistically modelling-and calibrating to extensive, country-specific data-the incidence of disease, health-seeking behaviour, and the capacity of the healthcare system to meet the demand for care under realistic constraints on human resources for health available, we were able to simulate the health gains achievable under a number of plausible HBP strategies for the country. We found that the HBP emerging from a linear constrained optimisation analysis (LCOA) achieved the largest health gain-∼8% reduction in disability adjusted life years (DALYs) between 2023 and 2042 compared to the benchmark scenario-by concentrating resources on high-impact treatments. This HBP however incurred a relative excess in DALYs in the first few years of its implementation. Other feasible approaches to prioritisation were assessed, including service prioritisation based on patient characteristics, rather than service type. Unlike the LCOA-based HBP, this approach achieved consistent health gains relative to the benchmark scenario on a year- to-year basis, and a 5% reduction in DALYs over the whole period, which suggests an approach based upon patient characteristics might prove beneficial in the future.

Health workforce needs in Malawi: analysis of the Thanzi La Onse integrated epidemiological model of care.

BACKGROUND: To make the best use of health resources, it is crucial to understand the healthcare needs of a population-including how needs will evolve and respond to changing epidemiological context and patient behaviour-and how this compares to the capabilities to deliver healthcare with the existing workforce. Existing approaches to planning either rely on using observed healthcare demand from a fixed historical period or using models to estimate healthcare needs within a narrow domain (e.g., a specific disease area or health programme). A new data-grounded modelling method is proposed by which healthcare needs and the capabilities of the healthcare workforce can be compared and analysed under a range of scenarios: in particular, when there is much greater propensity for healthcare seeking. METHODS: A model representation of the healthcare workforce, one that formalises how the time of the different cadres is drawn into the provision of units of healthcare, was integrated with an individual-based epidemiological model-the Thanzi La Onse model-that represents mechanistically the development of disease and ill-health and patients' healthcare seeking behaviour. The model was applied in Malawi using routinely available data and the estimates of the volume of health service delivered were tested against officially recorded data. Model estimates of the "time needed" and "time available" for each cadre were compared under different assumptions for whether vacant (or established) posts are filled and healthcare seeking behaviour. RESULTS: The model estimates of volume of each type of service delivered were in good agreement with the available data. The "time needed" for the healthcare workforce greatly exceeded the "time available" (overall by 1.82-fold), especially for pharmacists (6.37-fold) and clinicians (2.83-fold). This discrepancy would be largely mitigated if all vacant posts were filled, but the large discrepancy would remain for pharmacists (2.49-fold). However, if all of those becoming ill did seek care immediately, the "time needed" would increase dramatically and exceed "time supply" (2.11-fold for nurses and midwives, 5.60-fold for clinicians, 9.98-fold for pharmacists) even when there were no vacant positions. CONCLUSIONS: The results suggest that services are being delivered in less time on average than they should be, or that healthcare workers are working more time than contracted, or a combination of the two. Moreover, the analysis shows that the healthcare system could become overwhelmed if patients were more likely to seek care. It is not yet known what the health consequences of such changes would be but this new model provides-for the first time-a means to examine such questions.

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

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).

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

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.

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

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.

COVID-19 in Japan, January-March 2020: insights from the first three months of the epidemic.

BACKGROUND: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. METHODS: We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. RESULTS: The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16-23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms. CONCLUSIONS: Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.

Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts and population-based survey data.

INTRODUCTION: Model-based estimates of key HIV indicators depend on past epidemic trends that are derived based on assumptions about HIV disease progression and mortality in the absence of antiretroviral treatment (ART). Population-based HIV Impact Assessment (PHIA) household surveys conducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIV infection. CD4 cell counts measured in these individuals provide novel information to estimate HIV disease progression and mortality rates off ART. METHODS: We used Bayesian multi-parameter evidence synthesis to combine data on (1) cross-sectional CD4 cell counts among untreated adults living with HIV from 10 PHIA surveys, (2) survival after HIV seroconversion in East African seroconverter cohorts, (3) post-seroconversion CD4 counts and (4) mortality rates by CD4 count predominantly from European, North American and Australian seroconverter cohorts. We used incremental mixture importance sampling to estimate HIV natural history and ART uptake parameters used in the Spectrum software. We validated modelled trends in CD4 count at ART initiation against ART initiator cohorts in sub-Saharan Africa. RESULTS: Median untreated HIV survival decreased with increasing age at seroconversion, from 12.5 years [95% credible interval (CrI): 12.1-12.7] at ages 15-24 to 7.2 years (95% CrI: 7.1-7.7) at ages 45-54. Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV-related mortality rates. Our estimates suggested a weaker association between ART uptake and HIV-related mortality rates than previously assumed in Spectrum. Modelled CD4 counts in untreated people living with HIV matched recent household survey data well, though some intercountry variation in frequencies of CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation were comparable to data from ART initiator cohorts. An alternate model that stratified progression and mortality rates by sex did not improve model fit appreciably. CONCLUSIONS: Synthesis of multiple data sources results in similar overall survival as previous Spectrum parameter assumptions but implies more rapid progression and longer survival in lower CD4 categories. New natural history parameter values improve consistency of model estimates with recent cross-sectional CD4 data and trends in CD4 counts at ART initiation.

Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study.

BACKGROUND: COVID-19 has the potential to cause substantial disruptions to health services, due to cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions to services for HIV, tuberculosis, and malaria in low-income and middle-income countries with high burdens of these diseases could lead to additional loss of life over the next 5 years. METHODS: Assuming a basic reproduction number of 3·0, we constructed four scenarios for possible responses to the COVID-19 pandemic: no action, mitigation for 6 months, suppression for 2 months, or suppression for 1 year. We used established transmission models of HIV, tuberculosis, and malaria to estimate the additional impact on health that could be caused in selected settings, either due to COVID-19 interventions limiting activities, or due to the high demand on the health system due to the COVID-19 pandemic. FINDINGS: In high-burden settings, deaths due to HIV, tuberculosis, and malaria over 5 years could increase by up to 10%, 20%, and 36%, respectively, compared with if there was no COVID-19 pandemic. The greatest impact on HIV was estimated to be from interruption to antiretroviral therapy, which could occur during a period of high health system demand. For tuberculosis, the greatest impact would be from reductions in timely diagnosis and treatment of new cases, which could result from any prolonged period of COVID-19 suppression interventions. The greatest impact on malaria burden could be as a result of interruption of planned net campaigns. These disruptions could lead to a loss of life-years over 5 years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV and tuberculosis epidemics. INTERPRETATION: Maintaining the most critical prevention activities and health-care services for HIV, tuberculosis, and malaria could substantially reduce the overall impact of the COVID-19 pandemic. FUNDING: Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development, and Medical Research Council.

Determinants of survival of people living with HIV/AIDS on antiretroviral therapy in Brazil 2006-2015.

BACKGROUND: We compared AIDS-related mortality rates in people living with HIV (PLHIV) starting antiretroviral therapy (ART) in Brazil during 2006-2015 and examined associated risk factors . METHODS: Data on ART use in PLHIV and AIDS mortality in Brazil was analysed with piecewise constant exponential models. Mortality rates and hazard ratios were estimated for 0-6, 6-12, 13-24, 25-36 and > 36 months of ART use and adjusted for region, age, sex, baseline CD4 cell count and calendar year of ART initiation. An additional analysis restricted to those with data on risk group was also performed. RESULTS: 269,076 individuals were included in the analysis, 165,643 (62%) males and 103,433 (38%) females, with 1,783,305 person-years of follow-up time. 21,749 AIDS deaths were reported and 8898 deaths occurred in the first year of ART. The risk of death in the first six months decreased with early ART initiation; those starting treatment early with CD4 > 500 cells per µL had a hazard ratio of 0.06 (95% CI 0.05-0.07) compared with CD4 < 200 cells per µL. Older age, male sex, intravenous drug use and starting treatment in earlier calendar years were associated with higher mortality rates. People living in the North, Northeast and South of Brazil experienced significantly higher AIDS mortality rates than those in the Southeast (HR 1.44, [95% CI 1.35-1.54], 1.10 [1.05-1.16] and 1.22 [1.17-1.28] respectively). CONCLUSIONS: Early treatment is likely to have contributed to the improved survival in PLHIV on ART, with the greatest benefits observed in women, younger age-groups and those living in the North.

Estimating HIV incidence from surveillance data indicates a second wave of infections in Brazil.

Emerging evidence suggests that HIV incidence rates in Brazil, particularly among men, may be rising. Here we use Brazil's integrated health systems data to develop a mathematical model, reproducing the complex surveillance systems and providing estimates of HIV incidence, number of people living with HIV (PLHIV), reporting rates and ART initiation rates. An age-structured deterministic model with a flexible spline was used to describe the natural history of HIV along with reporting and treatment rates. Individual-level surveillance data for 1,077,295 cases (HIV/AIDS diagnoses, ART dispensations, CD4 counts and HIV/AIDS-related deaths) were used to calibrate the model using Bayesian inference. The results showed a second wave of infections occurring after 2001 and 56,000 (95% Credible Interval 43,000-71,000) new infections in 2015, 37,000 (95% CrI 28,000-54,000) infections in men and 16,000 (95% CrI 10,000-23,000) in women. The estimated number of PLHIV by end-2015 was 838,000 (95% CrI 675,000-1,083,000), with 80% (95% CrI 62-98%) of those individuals reported to the Ministry of Health. Women were more likely to be diagnosed and reported than men; 86.8% of infected women had been reported compared with 75.7% of men. Likewise, ART initiation rates for women were higher than those for men. The second wave contradicts previous estimates of HIV incidence trends in Brazil and there were persistent differences in the rates of accessing care between men and women. Nevertheless, the Brazilian HIV program has achieved high rates of detection and treatment, making considerable progress over the past ten years.

Joint estimation of CD4+ cell progression and survival in untreated individuals with HIV-1 infection.

OBJECTIVE: We compiled the largest dataset of seroconverter cohorts to date from 25 countries across Africa, North America, Europe, and Southeast/East (SE/E) Asia to simultaneously estimate transition rates between CD4 cell stages and death, in antiretroviral therapy (ART)-naive HIV-1-infected individuals. DESIGN: A hidden Markov model incorporating a misclassification matrix was used to represent natural short-term fluctuations and measurement errors in CD4 cell counts. Covariates were included to estimate the transition rates and survival probabilities for each subgroup. RESULTS: The median follow-up time for 16 373 eligible individuals was 4.1 years (interquartile range 1.7-7.1), and the mean age at seroconversion was 31.1 years (SD 8.8). A total of 14 525 individuals had recorded CD4 cell counts pre-ART, 1885 died, and 6947 initiated ART. Median (interquartile range) survival for men aged 20 years at seroconversion was 13.0 (12.4-13.4), 11.6 (10.9-12.3), and 8.3 years (7.9-8.9) in Europe/North America, Africa, and SE/E Asia, respectively. Mortality rates increase with age (hazard ratio 2.22, 95% confidence interval 1.84-2.67 for >45 years compared with <25 years) and vary by region (hazard ratio 2.68, 1.75-4.12 for Africa and 1.88, 1.50-2.35 for Asia compared with Europe/North America). CD4 cell decline was significantly faster in Asian cohorts compared with Europe/North America (hazard ratio 1.45, 1.36-1.54). CONCLUSION: Mortality and CD4 cell progression rates exhibited regional and age-specific differences, with decreased survival in African and SE/E Asian cohorts compared with Europe/North America and in older age groups. This extensive dataset reveals heterogeneities between regions and ages, which should be incorporated into future HIV models.

Spatial Dynamics and High Risk Transmission Pathways of Poliovirus in Nigeria 2001-2013.

The polio eradication programme in Nigeria has been successful in reducing incidence to just six confirmed cases in 2014 and zero to date in 2015, but prediction and management of future outbreaks remains a concern. A Poisson mixed effects model was used to describe poliovirus spread between January 2001 and November 2013, incorporating the strength of connectivity between districts (local government areas, LGAs) as estimated by three models of human mobility: simple distance, gravity and radiation models. Potential explanatory variables associated with the case numbers in each LGA were investigated and the model fit was tested by simulation. Spatial connectivity, the number of non-immune children under five years old, and season were associated with the incidence of poliomyelitis in an LGA (all P < 0.001). The best-fitting spatial model was the radiation model, outperforming the simple distance and gravity models (likelihood ratio test P < 0.05), under which the number of people estimated to move from an infected LGA to an uninfected LGA was strongly associated with the incidence of poliomyelitis in that LGA. We inferred transmission networks between LGAs based on this model and found these to be highly local, largely restricted to neighbouring LGAs (e.g. 67.7% of secondary spread from Kano was expected to occur within 10 km). The remaining secondary spread occurred along routes of high population movement. Poliovirus transmission in Nigeria is predominantly localised, occurring between spatially contiguous areas. Outbreak response should be guided by knowledge of high-probability pathways to ensure vulnerable children are protected.

Key issues in the persistence of poliomyelitis in Nigeria: a case-control study.

BACKGROUND: The completion of poliomyelitis eradication is a global emergency for public health. In 2012, more than 50% of the world's cases occurred in Nigeria following an unanticipated surge in incidence. We aimed to quantitatively analyse the key factors sustaining transmission of poliomyelitis in Nigeria and to calculate clinical efficacy estimates for the oral poliovirus vaccines (OPV) currently in use. METHODS: We used acute flaccid paralysis (AFP) surveillance data from Nigeria collected between January, 2001, and December, 2012, to estimate the clinical efficacies of all four OPVs in use and combined this with vaccination coverage to estimate the effect of the introduction of monovalent and bivalent OPV on vaccine-induced serotype-specific population immunity. Vaccine efficacy was determined using a case-control study with CIs based on bootstrap resampling. Vaccine efficacy was also estimated separately for north and south Nigeria, by age of the children, and by year. Detailed 60-day follow-up data were collected from children with confirmed poliomyelitis and were used to assess correlates of vaccine status. We also quantitatively assessed the epidemiology of poliomyelitis and programme performance and considered the reasons for the high vaccine refusal rate along with risk factors for a given local government area reporting a case. FINDINGS: Against serotype 1, both monovalent OPV (median 32.1%, 95% CI 26.1-38.1) and bivalent OPV (29.5%, 20.1-38.4) had higher clinical efficacy than trivalent OPV (19.4%, 16.1-22.8). Corresponding data for serotype 3 were 43.2% (23.1-61.1) and 23.8% (5.3-44.9) compared with 18.0% (14.1-22.1). Combined with increases in coverage, this factor has boosted population immunity in children younger than age 36 months to a record high (64-69% against serotypes 1 and 3). Vaccine efficacy in northern states was estimated to be significantly lower than in southern states (p≤0.05). The proportion of cases refusing vaccination decreased from 37-72% in 2008 to 21-51% in 2012 for routine and supplementary immunisation, and most caregivers cited ignorance of either vaccine importance or availability as the main reason for missing routine vaccinations (32.1% and 29.6% of cases, respectively). Multiple regression analyses highlighted associations between the age of the mother, availability of OPV at health facilities, and the primary source of health information and the probability of receiving OPV (all p<0.05). INTERPRETATION: Although high refusal rates, low OPV campaign awareness, and heterogeneous population immunity continued to support poliomyelitis transmission in Nigeria at the end of 2012, overall population immunity had improved due to new OPV formulations and improvements in programme delivery. FUNDING: Bill & Melinda Gates Foundation Vaccine Modeling Initiative, Royal Society.

The potential impact of routine immunization with inactivated poliovirus vaccine on wild-type or vaccine-derived poliovirus outbreaks in a posteradication setting.

The "endgame" for worldwide poliomyelitis eradication will entail eventual cessation of the use of oral poliovirus vaccine (OPV) in all countries to prevent the reintroduction of vaccine-derived polioviruses--exposing some populations to an unprecedented, albeit low, risk of poliovirus outbreaks. Inactivated poliovirus vaccine (IPV) is likely to play a large part in post--OPV management of poliovirus risks by reducing the consequences of any reintroduction of poliovirus. In this article, we examine the impact IPV would have on an outbreak in a partially susceptible population after OPV cessation, using a mathematical model of poliovirus transmission with a realistic natural history and case reporting. We explore a range of assumptions about the impact of IPV on an individual's infectiousness, given the lack of knowledge about this parameter. We show that routine use of IPV is beneficial under most conditions, increasing the chance of fadeout and reducing the expected prevalence of infection at the time of detection. The duration of "silent" poliovirus circulation prior to detection lengthens with increasing coverage of IPV, although this only increases the expected prevalence of infection at the time of the OPV response if IPV has a very limited impact on infectiousness. Overall, the model predicts that routine use of IPV will be advantageous for the posteradication management of poliovirus.

Predicting the impact of long-term temperature changes on the epidemiology and control of schistosomiasis: a mechanistic model.

BACKGROUND: Many parasites of medical and veterinary importance are transmitted by cold-blooded intermediate hosts or vectors, the abundance of which will vary with ambient temperatures, potentially altering disease prevalence. In particular, if global climate change will increase mean ambient temperature in a region endemic with a human pathogen then it is possible that the incidence of disease will similarly increase. Here we examine this possibility by using a mathematical model to explore the effects of increasing long-term mean ambient temperature on the prevalence and abundance of the parasite Schistosoma mansoni, the causative agent of schistosomiasis in humans. PRINCIPAL FINDINGS: The model showed that the impact of temperature on disease prevalence and abundance is not straightforward; the mean infection burden in humans increases up to 30 degrees C, but then crashes at 35 degrees C, primarily due to increased mortalities of the snail intermediate host. In addition, increased temperatures changed the dynamics of disease from stable, endemic infection to unstable, epidemic cycles at 35 degrees C. However, the prevalence of infection was largely unchanged by increasing temperatures. Temperature increases also affected the response of the model to changes in each parameter, indicating certain control strategies may become less effective with local temperature changes. At lower temperatures, the most effective single control strategy is to target the adult parasites through chemotherapy. However, as temperatures increase, targeting the snail intermediate hosts, for example through molluscicide use, becomes more effective. CONCLUSIONS: These results show that S. mansoni will not respond to increased temperatures in a linear fashion, and the optimal control strategy is likely to change as temperatures change. It is only through a mechanistic approach, incorporating the combined effects of temperature on all stages of the life-cycle, that we can begin to predict the consequences of climate change on the incidence and severity of such diseases.