Seasonality of confirmed malaria cases from 2008 to 2017 in Togo: a time series analysis by health district and target group

Background This study aimed to assess the seasonality of confirmed malaria cases in Togo and to provide new indicators of malaria seasonality to the National Malaria Control Programme (NMCP). Methods Aggregated data of confirmed malaria cases were collected monthly from 2008 to 2017 by the Togo’s NMCP and stratified by health district and according to three target groups: children < 5 years old, children ≥ 5 years old and adults, and pregnant women. Time series analysis was carried out for each target group and health district. Seasonal decomposition was used to assess the seasonality of confirmed malaria cases. Maximum and minimum seasonal indices, their corresponding months, and the ratio of maximum/minimum seasonal indices reflecting the importance of malaria transmission, were provided by health district and target group. Results From 2008 to 2017, 7,951,757 malaria cases were reported in Togo. Children < 5 years old, children ≥ 5 years old and adults, and pregnant women represented 37.1%, 57.7% and 5.2% of the confirmed malaria cases, respectively. The maximum seasonal indices were observed during or shortly after a rainy season and the minimum seasonal indices during the dry season between January and April in particular. In children < 5 years old, the ratio of maximum/minimum seasonal indices was higher in the north, suggesting a higher seasonal malaria transmission, than in the south of Togo. This is also observed in the other two groups but to a lesser extent. Conclusions This study contributes to a better understanding of malaria seasonality in Togo. The indicators of malaria seasonality could allow for more accurate forecasting in malaria interventions and supply planning throughout the year.

Practices of anti-malaria pharmaceuticals inventory control system and associated challenges in public health facilities of Oromiya special zone, Amhara region, Ethiopia

Background Anti-malaria pharmaceuticals inventory control system helps to maintain an appropriate stock level using logistics management information system records and reports. Antimalaria pharmaceuticals are highly influenced by seasonality and demand variation. Thus, to compensate the seasonality, resupply quantities should be adjusted by multiplying the historical consumption with the Look-ahead seasonality indexes (LSI) to minimize stock-outs during the peak transmission season and overstocks (possible expiries) during off-peak seasons The purpose of this study was to assess anti-malaria pharmaceuticals inventory control practice and associated challenges in public health facilities of the Oromiya special zone, Amhara region, Ethiopia. Methodology Facility-based cross-sectional study design employing both quantitative and qualitative methods, explanatory sequential mixed method, of data collection and analysis was used in all public health facilities in the Oromia special zone from September 1 to September 30, 2019. The study was conducted in 27 health centers and 2 hospitals, the dispensing units managing anti-malaria pharmaceuticals and data was collected using observation checklists The quantitative data were analyzed by Statistical package for social sciences using linear regression. Purposive sampling was used to select key informants and 12 in-depth interviews were conducted by the principal investigator. Thematic analysis was performed using Nvivo 11 plus and interpretation by narrative strategies. Results The quantitative finding in this study revealed that none of the health facilities surveyed calculated months of stock and multiplied the historical consumption with look ahead seasonal indices (LSI) to forecast the upcoming year consumptions.. Average months of stock of anti-malaria pharmaceuticals were 5.32 months with the annual wastage rate of 11.32%. The point and periodic availability of anti-malaria pharmaceuticals was 72.38 and 77.03% respectively. The number of stocks out days within the previous 6 months was 41.34 days. The study also reported bin card usage (β = − 3.5, p = 0.04) and availability of daily dispensing register (β = − 2.7, p = 0.005) had statistically significant effect on anti-malaria pharmaceuticals inventory control practice. The perceived challenges attributed to the poor anti-malaria pharmaceuticals inventory control practice were lack of integrated pharmaceutical logistics system training, management support, inadequate and near expiry supply from pharmaceuticals supply agency, job dissatisfaction, and staff turnover. Conclusion Inventory control practices for anti-malaria pharmaceuticals was poor as indicated by maximum stock level and none of the health facilities calculated months of stock and the previous consumption was not multiplied by look ahead seasonal indices to compensate the seasonal and demand variation. Efforts should be under-taken by concerned bodies to improve inventory control practice; such as training and regular follow up have to be provided to the health professionals managing anti-malaria pharmaceuticals.

Behaviour of Prices of Groundnut in Northern Hills of Chhattisgarh

This study attempted to guide the farmers and planners for reliable and specific information concerning the prices of Groundnut in the Northern Hills agro-climatic zone of Chhattisgarh. The time series data of prices was taken monthly from January, 2010 to March, 2021 (135 months) and it was used to forecast the prices for upcoming 24 months i.e. April, 2021 to March, 2023. The time trend analysis of prices of groundnut were found sharpely increasing over the study period. The price remains almost similar over the year as indicated by seasonal indices. On the basis of lowest MAE, MAPE, RMSE and AIC, out of the seasonal ARIMA models we got, ARIMA (1,1,1) (0,0,2) [12] was best identified fitted model for predicting prices of Groundnut. The data analysis is done by using R ().

Road Traffic Offences in Nigeria: An Empirical Analysis using Buys-Ballot Approach

Road traffic offences in time series analysis when trend-cycle component is quadratic is discussed in this study. The study is to investigate the variance stability, trend pattern, seasonal indices and suitable model for decomposition of study data. The study shows that, the series is seasonal with evidence of upward trend or downward trend. There is an upsurge of the series in the months of March, August and November and a drop in January, June and December. The periodic standard deviations are stable while the seasonal standard deviations differ, suggesting that the series requires transformation to make the seasonal indices additive.

Analysis of Seasonal Price Fluctuations of Paddy (Boro) in Bangladesh

This paper has focused on seasonal variations of price and trend of the price escalation of paddy in Bangladesh using monthly average wholesale price of Boro paddy over a period from 2001 to 2019. Secondary data were used in this study and collected from different secondary sources. The multiplicative model was exercised in this study; the least square method was applied to find out the long-term changes occurring in the price of paddy and the ratio to moving average method was used to measure seasonal fluctuations in price of paddy. It was evidently observed from the study that seasonal fluctuations in price of paddy prevail in Bangladesh as seasonal indices were deviated from hundred in different months. April to August, the price of paddy was lower compare to other months’ price because April and Mayare the harvesting period of Boro paddy and resulted in more supply to the market. From August, it was increasing gradually and reached to the highest position on March with 112.15. Long-term trend analysis showed that prices of paddy will increase Tk. 72.80 per quintal higher annually compare to the country’s average price. SAARC J. Agri., 18(2): 219-226 (2020)

Trend and Seasonality Analysis in Prices and Arrivals of Selected Agricultural Commodities in India

The study was conducted to find the fluctuation in the prices and arrival of the selected high value agricultural commodities. The study was conducted for the period 2004-2020 by collecting secondary data from CMIE (Centre for Monitoring Indian Economy) database. The major agricultural commodities were selected purposively on the basis of high price fluctuatiion and arrivals in the market. The commodities selected for the study include, castor seed, coriander, jeera, soybean and turmeric. The results of the study showed that there is a positive and significant relationship between growth rate and the prices of selected commodities with Jeera showing the highest growth rate of (9.87%) in arrival followed by turmeric (9.05%) and the lowest in coriander (5.06%) as against the prices where it showed all together with a different scenario with highest in case of coriander (7.55%) followed by soybean (7.24%) and lowest in jeera with (5.69%) respectively. The results of the findings revealed that in all the commodities high seasonal indices were observed from March to June indicating high post-harvest arrivals during these months. In the case of soybean and turmeric, the seasonal index for prices is high in April to September, which reveals that there is a lack of storage facilities and the production during these months is very low. This study suggested improvement in the infrastructure, storage, and postharvest techniques so that the arrivals of these commodities get increased and availability should be throughout the year so that the price fluctuation can be minimized.

Acute Promyelocytic Leukemia (APL): Seasonal Behavior in Colombia for the Period 2009-2019

Background Acute promyelocytic leukemia (APL) is a malignant hematologic disease with a high cure rate, but unfortunately it produces several serious complications at the onset of the disease that explain the high early mortality. Based on clinical experience and the papers that precede this document, it has been observed that the incidence of this type of hematological cancer tends to increase at certain times of the year. The present study aims to determine the possible variations in the time intervals of the prevalence of promyelocytic leukemia in Colombia in the decade 2009 to 2019, in order to identify the behavior of the event, seasonality and cyclicality. Methods With data from the individual records of service provision (RIPS) of the official Colombian health system, the prevalence of APL in Colombia from 2009 to 2019 was identified. A filter was made by people attended, main diagnosis, C924 - promyelocytic leukemia acute, by year, semester and month. The analysis was performed with RStudio, R version 4.0.2 (2020-06-22); The fpp2 library was used, the analysis of the monthly and quarterly time series was carried out, the decomposition of the time series was carried out, trying through this process to evaluate the seasonal indices through additive and multiplicative types. Results During the entire period 2009 to 2019, 2,986 APL diagnoses were found throughout the national territory of Colombia. A progressive increase in prevalence was determined in the period studied (Graph 1). Cycles of increasing cases were observed every 10 months in the period 2009 to 2015 and in the cycle from 2016 to 2019 there was a prolongation of the cycle every 17 months, which strongly suggested that APL has cyclical behavior. Quarterly seasonality was identified by the multiplicative method with increases and decreases that behave in a similar way throughout the period studied (Graph 2). Conclusion APL is a highly curable disease that requires adequate support at the onset of the disease to avoid early mortality. The data from this study allow us to conclude that for the period 2009 to 2019 there is a seasonal behavior of this malignant hemopathy. The possibility of predicting during which months of the year the incidence of the disease will increase can serve to properly plan the health services in charge of treating this disease. Additional studies are required to determine what is the cause of the cyclical and seasonal behavior of this APL Disclosures Idrobo: Amgen:Honoraria, Speakers Bureau;Takeda:Honoraria, Speakers Bureau;Janssen:Honoraria, Speakers Bureau;Tecnofarma:Honoraria, Speakers Bureau;Abbvie:Honoraria, Speakers Bureau.

FIRST LARGE EXTENT AND HIGH RESOLUTION CROPLAND AND CROP TYPE MAP OF ARGENTINA

The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.

Spatio-temporal variation of nitrate and nitrite levels in groundwater samples from Romania

This study investigated the spatial and temporal distribution of nitrate and nitrite concentration in groundwater from different geographical regions, in Romania. A special emphasis was put on a descriptive statistical analysis of data, namely on the determination of seasonal indices during dry and wet seasons. Nitrate and nitrite concentrations were monitored in 24 groundwater sources situated in different areas, between January 2016 and February 2020. The obtained data showed that the values of nitrate concentrations were situated between 8.03 mg/L in the North-Eastern part of Romania, 6.37 mg/L in the South-Eastern part of the country, and 3.55 mg/L in the Western part towards the center of the country. Nitrite concentration values were situated under the national maximum admitted limit, 0.5 mg/L, in all the investigated areas. The obtained data shows small changes in water quality during the monitoring period, which leads to the conclusion that, in this long interval of time, there were no significant groundwater contaminations with nitrate and nitrite. For adequate control of water pollution and rigorous management of groundwater sources, seasonal indices were calculated.

Market Integration and Price Transmission amongst the Major Wholesale and Retail Markets of Lentil (Lens culinaris / Lens esculenta) in India

Background: India has become self-sufficient for cereal production but is still dependent upon pulse imports for fulfilling its domestic demands. These imports are very much capable of influencing the domestic prices, so the present study was undertaken to study the integration and price transmission amongst the major lentil producing states of India i.e. Madhya Pradesh, Uttar Pradesh, West Bengal, Bihar, Rajasthan and Assam. Methods: Out of these six states, altogether ten markets and all India average values were undertaken for the present study based on the quantum of lentil marketed and availability of data. The secondary data was collected from the Agmarknet portal for the lentil crop while Minitab and R software were used for the analysis of the retrieved data. Various techniques like Seasonal Indices (SI), unit-root test, Johansen's cointegration test and Granger causality test were applied to find the results and conclusions of this study. Result: The results have stated that the prices of these ten wholesale and retail markets are highly integrated and most of the markets have a uni-directional relationship with each other. The wholesale and retail markets of Jaipur and Lucknow have little/no relationship with the other markets while they have a bidirectional relationship between their own wholesale and retail market prices indicating that they might be the markets where prices are discovered, as they are not found to be influenced by the other spatially separated markets.