The impact of sustained malaria control in the Loreto region of Peru: a retrospective, observational, spatially-varying interrupted time series analysis of the PAMAFRO program

Background

Although malaria control investments worldwide have resulted in dramatic declines in transmission since 2000, progress has stalled. In the Amazon, malaria resurgence has followed withdrawal of Global Fund support of the Project for Malaria Control in Andean Border Areas (PAMAFRO). We estimate intervention-specific and spatially-explicit effects of the PAMAFRO program on malaria incidence across the Loreto region of Peru, and consider the influence of the environmental risk factors in the presence of interventions.

Methods

We conducted a retrospective, observational, spatial interrupted time series analysis of malaria incidence rates among people reporting to health posts across Loreto, Peru between the first epidemiological week of January 2001 and the last epidemiological week of December 2016. Model inference is at the smallest administrative unit (district), where the weekly number of diagnosed cases of Plasmodium vivax and Plasmodium falciparum were determined by microscopy. Census data provided population at risk. We include as covariates weekly estimates of minimum temperature and cumulative precipitation in each district, as well as spatially- and temporally-lagged malaria incidence rates. Environmental data were derived from a hydrometeorological model designed for the Amazon. We used Bayesian spatiotemporal modeling techniques to estimate the impact of the PAMAFRO program, variability in environmental effects, and the role of climate anomalies on transmission after PAMAFRO withdrawal.

Findings

During the PAMAFRO program, incidence of P. vivax declined from 42.8 to 10.1 cases/1000 people/year. Incidence for P. falciparum declined from 14.3 to 2.5 cases/1000 people/year over this same period. The effects of PAMAFRO-supported interventions varied both by geography and species of malaria. Interventions were only effective in districts where interventions were also deployed in surrounding districts. Further, interventions diminished the effects of other prevailing demographic and environmental risk factors. Withdrawal of the program led to a resurgence in transmission. Increasing minimum temperatures and variability and intensity of rainfall events from 2011 onward and accompanying population displacements contributed to this resurgence.

Interpretation

Malaria control programs must consider the climate and environmental scope of interventions to maximize effectiveness. They must also ensure financial sustainability to maintain local progress and commitment to malaria prevention and elimination efforts, as well as to offset the effects of environmental change that increase transmission risk.

Funding

National Aeronautics and Space Administration, National Institutes of Health, Bill and Melinda Gates Foundation.

Madden-Julian Oscillation influence on sub-seasonal rainfall variability on the west of South America

The Madden-Julian Oscillation (MJO) is the leading driver of intraseasonal rainfall variability in the global tropics. However, the influence of MJO on western tropical South America (WTSA) has not been a focus of research. This is not surprising since the MJO convective core becomes nondescript as it propagates across the eastern Pacific, such that its influence on the Pacific coast of tropical South America is not obvious in global analyses. In this study, we examine MJO impacts on subseasonal rainfall variability in the rainiest season for WTSA (February-April). In order to avoid confusion with El Niño Southern Oscillation (ENSO) signals, only ENSO-neutral years are included in the analysis. We found that the MJO convective core reemerges when it propagates onto land in WTSA, and that it is associated with subseasonal precipitation anomalies of 20-50% relative to climatology. The MJO signal is evident in the Real-Time Multivariate MJO (RMM) index; however, the signal is clearer when a custom subseasonal index for the region based on WTSA outgoing longwave radiation is employed. Dynamically, the MJO influence is consistent with a modulation of the Pacific Ocean Walker Circulation descending branch, which is climatologically located in or near WTSA. Furthermore, MJO drives zonal and vertical motions on moisture and wind fields that influence precipitation in the region. We found that the timing of deep convection on subseasonal timescales captured by the regional index is consistent with a dominant role of the MJO convective core, rather than propagation of equatorial Rossby or Kelvin waves. However, there is evidence that equatorial Rossby waves that emerge over the tropical Atlantic Ocean also influence precipitation in WTSA on MJO timescales.

Spatiotemporal clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in Machala, Ecuador, in 2010

Background

Dengue fever, a mosquito-borne viral disease, is a rapidly emerging public health problem in Ecuador and throughout the tropics. However, we have a limited understanding of the disease transmission dynamics in these regions. Previous studies in southern coastal Ecuador have demonstrated the potential to develop a dengue early warning system (EWS) that incorporates climate and non-climate information. The objective of this study was to characterize the spatiotemporal dynamics and climatic and social-ecological risk factors associated with the largest dengue epidemic to date in Machala, Ecuador, to inform the development of a dengue EWS.

Methods

The following data from Machala were included in analyses: neighborhood-level georeferenced dengue cases, national census data, and entomological surveillance data from 2010; and time series of weekly dengue cases (aggregated to the city-level) and meteorological data from 2003 to 2012. We applied LISA and Moran’s I to analyze the spatial distribution of the 2010 dengue cases, and developed multivariate logistic regression models through a multi-model selection process to identify census variables and entomological covariates associated with the presence of dengue at the neighborhood level. Using data aggregated at the city-level, we conducted a time-series (wavelet) analysis of weekly climate and dengue incidence (2003-2012) to identify significant time periods (e.g., annual, biannual) when climate co-varied with dengue, and to describe the climate conditions associated with the 2010 outbreak.

Results

We found significant hotspots of dengue transmission near the center of Machala. The best-fit model to predict the presence of dengue included older age and female gender of the head of the household, greater access to piped water in the home, poor housing condition, and less distance to the central hospital. Wavelet analyses revealed that dengue transmission co-varied with rainfall and minimum temperature at annual and biannual cycles, and we found that anomalously high rainfall and temperatures were associated with the 2010 outbreak.

Conclusions

Our findings highlight the importance of geospatial information in dengue surveillance and the potential to develop a climate-driven spatiotemporal prediction model to inform disease prevention and control interventions. This study provides an operational methodological framework that can be applied to understand the drivers of local dengue risk.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0610-4) contains supplementary material, which is available to authorized users.