Dataset Information

Assessment of climate-driven variations in malaria incidence in Swaziland: toward malaria elimination.

ABSTRACT:

Background

Swaziland aims to eliminate malaria by 2020. However, imported cases from neighbouring endemic countries continue to sustain local parasite reservoirs and initiate transmission. As certain weather and climatic conditions may trigger or intensify malaria outbreaks, identification of areas prone to these conditions may aid decision-makers in deploying targeted malaria interventions more effectively.

Methods

Malaria case-surveillance data for Swaziland were provided by Swaziland's National Malaria Control Programme. Climate data were derived from local weather stations and remote sensing images. Climate parameters and malaria cases between 2001 and 2015 were then analysed using seasonal autoregressive integrated moving average models and distributed lag non-linear models (DLNM).

Results

The incidence of malaria in Swaziland increased between 2005 and 2010, especially in the Lubombo and Hhohho regions. A time-series analysis indicated that warmer temperatures and higher precipitation in the Lubombo and Hhohho administrative regions are conducive to malaria transmission. DLNM showed that the risk of malaria increased in Lubombo when the maximum temperature was above 30 °C or monthly precipitation was above 5 in. In Hhohho, the minimum temperature remaining above 15 °C or precipitation being greater than 10 in. might be associated with malaria transmission.

Conclusions

This study provides a preliminary assessment of the impact of short-term climate variations on malaria transmission in Swaziland. The geographic separation of imported and locally acquired malaria, as well as population behaviour, highlight the varying modes of transmission, part of which may be relevant to climate conditions. Thus, the impact of changing climate conditions should be noted as Swaziland moves toward malaria elimination.

SUBMITTER: Chuang TW

PROVIDER: S-EPMC5455096 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe potential contribution of knowledge, attitudes and practices (KAP) studies to malaria research and control has not received much attention in most southern African countries. This study investigated the local communities' understanding of malaria transmission, recognition of signs and symptoms, perceptions of cause, treatment-seeking patterns, preventive measures and practices in order to inform the country's proposed malaria elimination programme in Swaziland.MethodsA descriptive cross-sectional survey was undertaken in four Lubombo Spatial Development Initiative (LSDI) sentinel sites in Swaziland. These sentinel sites share borders with Mozambique. A structured questionnaire was administered to 320 randomly selected households. Only one adult person was interviewed per household. The interviewees were the heads of households and in the absence of the heads of households responsible adults above 18 years were interviewed.ResultsA substantial number of research participants showed reasonable knowledge of malaria, including correct association between malaria and mosquito bites, its potential fatal consequences and correct treatment practices. Almost 90% (n = 320) of the respondents stated that they would seek treatment within 24 hours of onset of malaria symptoms, with health facilities as their first treatment option. Most people (78%) perceived clinics and vector control practices as central to treating and preventing malaria disease. Indoor residual spraying (IRS) coverage and bed net ownership were 87.2% and 38.8%, respectively. IRS coverage was in agreement with the World Health Organization's (WHO) recommendation of more than 80% within the targeted communities.ConclusionDespite fair knowledge of malaria in Swaziland, there is a need for improving the availability of information through the preferred community channels, such as tinkhundlas (districts), as well as professional health routes. This recommendation emerges along with the documented evidence suggesting that as the level transmission and disease decreases so does the perception about the importance of malaria control activities. Finally, given the relatively moderate ownership of bed net there is a need for future studies to evaluate the distribution of insecticide-treated nets (ITNs) compared with IRS.

Project description:BackgroundThe Malaria Elimination Demonstration Project (MEDP) maintained a workforce of 235 Village Malaria Workers (VMWs) and 25 Malaria Field Coordinators (MFCs) to conduct disease surveillance, case management, IEC/BCC activities, capacity building, and monitoring of vector control activities in 1233 villages of Mandla, a high malaria endemic district of Madhya Pradesh in central India.MethodsThe induction training was conducted for 3 days on malaria diagnosis, treatment, prevention, and ethics. All trainings were assessed using a pre and post-training assessment questionnaire, with 70% marks as qualifying threshold. The questionnaire was divided into three thematic areas viz. general knowledge related to malaria (KAP), diagnosis and treatment (DXRX), and vector control (PVC).ResultsIn 2017, the project trained 330 candidates, followed by 243 and 247 candidates in 2018 and 2019, respectively. 94.3% candidates passed after a single training session. Almost all (95%) candidates showed improvement in knowledge after the training with 4% showing no effect and 1% showing deterioration. Progressive improvement in scores of 2017 cohort was seen along with significant improvement in performance of candidates in 2019 after the introduction of systematic monitoring and 'shadowing' training exercises.ConclusionThe project has successfully demonstrated the value of recruitment of workers from the study area, outcome of training, and performance evaluation of field staff in malaria elimination programme. This careful strategy of recruitment and training resulted in a work-force that was capable of independently conducting surveillance, case management, vector control, and Information Education Communication/Behaviour Change Communication (IEC/BCC). The learnings of this study, including the training modules and monitoring processes, can be used to train the health delivery staff for achieving national goal for malaria elimination by 2030. Similar training and monitoring programmes could also be used for other public health delivery programmes.

Project description:Given the crucial role of climate in malaria transmission, many mechanistic models of malaria represent vector biology and the parasite lifecycle as functions of climate variables in order to accurately capture malaria transmission dynamics. Lower dimension mechanistic models that utilize implicit vector dynamics have relied on indirect climate modulation of transmission processes, which compromises investigation of the ecological role played by climate in malaria transmission. In this study, we develop an implicit process-based malaria model with direct climate-mediated modulation of transmission pressure borne through the Entomological Inoculation Rate (EIR). The EIR, a measure of the number of infectious bites per person per unit time, includes the effects of vector dynamics, resulting from mosquito development, survivorship, feeding activity and parasite development, all of which are moderated by climate. We combine this EIR-model framework, which is driven by rainfall and temperature, with Bayesian inference methods, and evaluate the model's ability to simulate local transmission across 42 regions in Rwanda over four years. Our findings indicate that the biologically-motivated, EIR-model framework is capable of accurately simulating seasonal malaria dynamics and capturing of some of the inter-annual variation in malaria incidence. However, the model unsurprisingly failed to reproduce large declines in malaria transmission during 2018 and 2019 due to elevated anti-malaria measures, which were not accounted for in the model structure. The climate-driven transmission model also captured regional variation in malaria incidence across Rwanda's diverse climate, while identifying key entomological and epidemiological parameters important to seasonal malaria dynamics. In general, this new model construct advances the capabilities of implicitly-forced lower dimension dynamical malaria models by leveraging climate drivers of malaria ecology and transmission.

Project description:BACKGROUND:Malaria transmission is influenced by a complex interplay of factors including climate, socio-economic, environmental factors and interventions. Malaria control efforts across Africa have shown a mixed impact. Climate driven factors may play an increasing role with climate change. Efforts to strengthen routine facility-based monthly malaria data collection across Africa create an increasingly valuable data source to interpret burden trends and monitor control programme progress. A better understanding of the association with other climatic and non-climatic drivers of malaria incidence over time and space may help guide and interpret the impact of interventions. METHODS:Routine monthly paediatric outpatient clinical malaria case data were compiled from 27 districts in Malawi between 2004 and 2017, and analysed in combination with data on climatic, environmental, socio-economic and interventional factors and district level population estimates. A spatio-temporal generalized linear mixed model was fitted using Bayesian inference, in order to quantify the strength of association of the various risk factors with district-level variation in clinical malaria rates in Malawi, and visualized using maps. RESULTS:Between 2004 and 2017 reported childhood clinical malaria case rates showed a slight increase, from 50 to 53 cases per 1000 population, with considerable variation across the country between climatic zones. Climatic and environmental factors, including average monthly air temperature and rainfall anomalies, normalized difference vegetative index (NDVI) and RDT use for diagnosis showed a significant relationship with malaria incidence. Temperature in the current month and in each of the 3 months prior showed a significant relationship with the disease incidence unlike rainfall anomaly which was associated with malaria incidence at only three months prior. Estimated risk maps show relatively high risk along the lake and Shire valley regions of Malawi. CONCLUSION:The modelling approach can identify locations likely to have unusually high or low risk of malaria incidence across Malawi, and distinguishes between contributions to risk that can be explained by measured risk-factors and unexplained residual spatial variation. Also, spatial statistical methods applied to readily available routine data provides an alternative information source that can supplement survey data in policy development and implementation to direct surveillance and intervention efforts.